Genetic Markers Of True Low Birth Weight

ABSTRACT

The present application provides for a method of diagnosing TLBW via measurement of expression of various TLBW-related genes. The present application also provides kits for the diagnosis of TLBW in a subject. The present application also provides a method for determining the basis for appropriate therapy for a subject suffering from TLBW.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional application Ser.Nos. 60/735,087 filed Nov. 8, 2005, 60/814,672 filed Jun. 16, 2006,60/834,285 filed Jul. 28, 2006 and Ser. No. ______ not yet assignedfiled Oct. 25, 2006, each of which is incorporated by reference in itsentirety herein.

GRANT INFORMATION

The subject matter of this application was developed at least in partunder National Institutes of Health (NIEHS) Grant No. ES0110596, so thatthe United States government holds certain rights herein.

FIELD OF THE INVENTION

The present invention relates to a method of diagnosing true low birthweight (TLBW) in a subject, kits for the diagnosis of TLBW in a subject,and a method for determining the basis for appropriate therapy for asubject diagnosed with TLBW.

BACKGROUND OF THE INVENTION

Converging evidence demonstrates that the propensity to acquire certainadult diseases is influenced by factors that impinge upon the individualearly in life, as well as by genetic and environmental interactions inadulthood. Epidemiological studies indicate that various risk factors,such as sub-optimal nutrition during gestation, resulting in reducedrates of fetal growth and birth weight, is linked to increased risk forcardiovascular (CV) disease, diabetes, obesity, and mental illness laterin life. A parallel body of literature using animal models confirms thatrisk factors resulting in reduced rates of fetal growth and birth weightalso lead to disease susceptibility. Examples of these risk factorsinclude restricted uterine blood flow, alterations in the proportions ofprotein and carbohydrate in the maternal diet, and overall reductions inmaternal food availability. As adults, offspring born in theseexperiments express a variety of phenotypes including increased insulinresistance, increased fat deposition, and hyperphagia, and elevatedblood pressure (BP). It has also been found that compromised fetalgrowth leads to changes in autonomic nervous system development and thatthese effects can be seen soon after birth.

Low Birth Weight

During the earlier part of the twentieth century, low birth weight (LBW)was presumed to be caused by preterm delivery, sometimes referred to aspremature birth; the terms “LBW” and “premature” were often usedinterchangeably. However, epidemiologic data accumulated during the1950s and 1960s established a distinction between infants with low birthweight due to preterm delivery, and babies which were simplyconstitutionally small but otherwise healthy.

It is now recognized that low birth weight is not necessarily the resultof preterm birth. Low birth weight (LBW) is defined by the World HealthOrganization as a weight at birth of less than 5.5 pounds (2,500 grams),measured within the first hour following birth. This weight cut-off isbased upon epidemiological studies and observations, and is usedprimarily for comparative health statistics. A multitude of factors areimplicated as causes for low birth weight. These factors include, butare not limited to, the mother's nutrition (e.g., malnourishment,unbalanced diet, such as excessive carbohydrate diet or a poor proteindiet), lifestyle (e.g., alcohol, tobacco, or drug abuse), and health(e.g., infections, illness, genetic factors). LBW is particularlyprevalent in un-industrialized countries and impoverished areas, wherethe typical cause is malnourishment. While these factors may have anadverse affect on the infant's fetal growth and birth weight and resultin the adverse health effects associated with LBW, other factors existwhich may result in a smaller baby, but without associated adversehealth effects. These include, but are not limited to, the baby's sex,gestation time, and the mother's physical characteristics (e.g., height,weight). It is noted that because birth weight may vary based upon oneor more of these factors which are not associated with adverse healtheffects, a clinical weight cut-off value for use in diagnosing low birthweight may vary between regions, and possibly between individuals, toaccount for these factors. Thus, the WHO definition of LBW as less than5.5 pounds may miscategorize infants, excluding heavier infants who aresmaller than they should be, yet including healthy babies who weigh lessthan 5.5 pounds, for example, for genetic reasons.

Failure to identify infants whose birth weight is outside the WHOdefinition but who are smaller than they should be can have seriousconsequences, as true low birth weight (“TLBW”) is considered anindicator and predictor of health. TLBW has been shown to increase thelikelihood of child mortality and disability, including higher incidenceof morbidity and mortality from infectious disease and sudden infantdeath syndrome (SIDS), and has also been associated with an increasedincidence of adult diseases such as diabetes, hypertension, coronaryheart disease and other cardiovascular diseases, and stroke. Fromstudies of the effects of famine, TLBW is also known to be associatedwith an increased risk for a number of psychiatric disorders includingantisocial behavior, depression, and schizophrenia.

Intrauterine growth restriction (IUGR), sometimes referred to asintrauterine growth retardation, is a subtype of low birth weightcharacterized by constrained growth in the womb, and is typicallydefined as birth weight falling under the 10th percentile of gestationalage. IUGR infants may have normal gestational periods, and although theyfall within the lower range for their gestational age, their birthweight may exceed 5.5 pounds and therefore are not diagnosed as lowbirth weight. Causes of IUGR include, but are not limited to, abnormalor retarded growth of the uterus, abnormal or retarded formation of theplacenta, maternal malnutrition, illness and infection, multiplegestation, and various behavioral risk factors such as tobacco, alcohol,and drug abuse. Differential expression of maternally and paternallyimprinted genes has also been implicated in IUGR. McMinn et al.,Unbalanced Placental Expression of Imprinted Genes in Human IntrauterineGrowth Restriction, Placenta, 2006, (6-7):540-9 (electronic publicationon Aug. 24, 2005).

Fetal alcohol syndrome (FAS) is a subtype of low birth weightcharacterized by exposure to alcohol during gestation. FAS encompasses anumber of alcohol-related conditions which include, but are not limitedto, fetal alcohol effects (FAE), partial fetal alcohol syndrome (PFAS),alcohol related neurodevelopmental disorder (ARND), and alcohol relatedbirth defects (ARBD). A diagnosis of FAS typically consists of threecriteria: (1) characteristic facial features including a flattenedmidface, thin upper lip, indistinct/absent philtrum, and short eyeslits; (2) growth retardation characterized by low birth weight,sometimes characterized by height and/or weight below the 5thpercentile; and (3) central nervous system neurodevelopmentalabnormalities. A child suffering from FAS may display impaired finemotor skills, learning disabilities, and/or behavior disorders.

Current Diagnostic Methods

Presently, low birth weight is determined by measuring the newborninfant's weight within the first hour following birth. As noted above,although the generally accepted birth weight cut-off is 5.5 pounds, itis sometimes appropriate to utilize a different cut-off for differentpopulations or regions. However, regardless of the specific weight valueutilized, an absolute cut-off weight fails to distinguish betweeninfants who are pathologically low birth weight and normal, healthyinfants which are simply small. Similarly, it fails to identify infantswhich exceed 5.5 pounds but may still have reduced fetal growth andbirth weight, and may be at risk for the associated health problems.

Current Therapies

Currently, there are no specialized therapies and interventions forinfants diagnosed with TLBW. The standard procedure is to simply feedthe infant and make certain the infant is kept warm, and to administerantibiotics if necessary. Current therapies thus do not account for thespecific cause of the true low birth weight (e.g., insufficientcalories, low protein), and do not necessarily correct the underlyingdefects which may contribute to future health risks.

Thus, there is a need for a method which accurately and objectivelydiagnoses true LBW which does not utilize an absolute cut-off.Accordingly, the present application provides for a method of diagnosingTLBW via measurement of expression of various TLBW-related genes, forexample, in the placenta. The present application also provides kits forthe diagnosis of TLBW in a subject. The present application alsoprovides a method for determining the appropriate therapy for a subjectsuffering from TLBW.

SUMMARY OF THE INVENTION

The present invention relates to a method of diagnosing true low birthweight (“TLBW”) in a subject, kits for the diagnosis of TLBW in asubject, and methods of determining the basis for treatment for asubject diagnosed with TLBW. It is based, at least in part, on thediscovery that the level of insulin-like growth factor-1 (“IGF1”)expression (as measured in placental RNA) was decreased in TLBW infants,based on measurements of increased blood pressure and heart rateresponses to feeding and head-up tilting; and, on the discovery thatbabies with birth weights on the low end of the normal distribution, butnot classified as LBW or small for gestational age (SGA) by currentcriteria, and which had low levels of expression of both IGF1 and IGF2in their placentas, were thinner, had lower baseline heart rates, andhad increased heart rate responses to feeding, all potentiallyindicative of TLBW. It is further based, in part, on the discovery of anumber of “TLBW related genes,” the expression levels of whichsignificantly differ (are increased or decreased) from control levels inan animal model of TLBW.

The present invention provides a method of diagnosing TLBW comprising:(a) measuring the level of gene expression of one or more TLBW relatedgenes in a subject sample (preferably a placental tissue sample); (b)comparing measured expression of the TLBW related genes to a standard orcontrol; wherein a change in gene expression characterized by a p-value,relative to gene expression in a healthy subject, which is less than orequal to 0.1, less than or equal to 0.05, less than or equal to 0.01, orless than or equal to 0.001 indicates a diagnosis of true low birthweight. The standard or control may be one or more samples derived fromone or more healthy, non-TLBW infant. Although the sample is preferablyplacenta, the subject sample may be derived from any source which mayprovide fetal or infant tissue or fluid, and may include maternal tissueand/or blood samples. In a preferred embodiment, gene expression ismeasured by a DNA chip or quantitative real-time polymerase chainreaction (PCR).

The method of the present invention may be used to evaluate the statusof a subject believed to be at risk for true low birth weight. Riskfactors for true low birth weight include, but are not limited to, amother's poor nutrition (e.g., malnourishment, caloric restriction,unbalanced diet, such as excessive carbohydrate diet or a poor proteindiet), lifestyle (e.g., alcohol, tobacco, or drug abuse), and/or health(e.g., infections, illness, genetic factors).

In another embodiment, the TLBW related genes are selected from thegroup consisting of genes encoding an insulin-like growth factor (“IGF,”e.g., IGF1, IGF2), and/or genes encoding IGF binding proteins (e.g.,ALS, CTGF/CCN2, Endocan, IGFBP-1, IGFBP-2, IGFBP-3, IGFBP-4, IGFBP-5,IGFBP-6, IGFBP-7, Nov/CCN3), and genes encoding IGF receptors. In apreferred embodiment, the gene expression of more than one gene isevaluated. Certain embodiments include determining the level of IGF geneexpression levels; other embodiments do not include determining thelevel of IGF gene expression levels. Genes which may be used in thepresent invention may be selected from the genes represented in Tables1, 2, 6, 7, 10, 11, 12, and/or 13. It will be known to a person ofordinary skill in the art that sequence homology between the rat genesand the human equivalents will allow extrapolation of this data for usein humans and other species. Based upon this information, a person ofordinary skill in the art will be capable of selecting genes whichdisplay an increase or decrease in gene expression.

In another non-limiting embodiment, the present invention provides amethod of diagnosing fetal alcohol syndrome (FAS) comprising: (a)measuring the level of gene expression of one or more FAS related genesin a subject sample (preferably a placental tissue sample); (b)comparing measured expression of the FAS related genes to a standard orcontrol; wherein a change in gene expression characterized by a p-value,relative to gene expression in a healthy subject, which is less than orequal to 0.1, less than or equal to 0.05, less than or equal to 0.01, orless than or equal to 0.001 indicates a diagnosis of fetal alcoholsyndrome. Genes which may be used in the present invention to diagnosefetal alcohol syndrome may be selected from the genes represented inTables 1, 2, 6, 7, 10, 11, 12, and/or 13, and are preferably selectedfrom Tables 11, 12, and/or 13. The standard or control may be one ormore samples derived from one or more healthy, non-FAS infant. Althoughthe sample is preferably placenta, the subject sample may be derivedfrom any source which may provide fetal or infant tissue or fluid, andmay include maternal tissue and/or blood samples. In a preferredembodiment, gene expression is measured by a DNA chip or quantitativereal-time polymerase chain reaction (PCR).

The present invention provides for a kit for diagnosis of true low birthweight comprising: (1) one or more oligonucleotide probes directed totrue low birth weight related genes; (2) reagents and equipment formeasuring gene expression; and (3) control reagents. The kit mayoptionally include reagents and equipment for the collection of thetissues and fluids required for these determinations. In one embodiment,the oligonucleotide probes may bind to genes selected from the groupconsisting of genes encoding an insulin-like growth factor (“IGF,” e.g.,IGF1, IGF2), and/or genes encoding IGF binding proteins (e.g., ALS,CTGF/CCN2, Endocan, IGFBP-1, IGFBP-2, IGFBP-3, IGFBP-4, IGFBP-5,IGFBP-6, IGFBP-7, Nov/CCN3), and/or genes encoding IGF receptors. Inanother embodiment, the oligonucleotide probes may bind to genesselected from the genes represented in Tables 1, 2, 6, 7, 10, 11, 12,and/or 13.

The present invention provides for a kit for diagnosis of fetal alcoholsyndrome (FAS) comprising: (1) one or more oligonucleotide probesdirected to fetal alcohol syndrome related genes; (2) reagents andequipment for measuring gene expression; and (3) control reagents. Thekit may optionally include reagents and equipment for the collection ofthe tissues and fluids required for these determinations. In oneembodiment, the oligonucleotide probes may bind to genes selected fromthe genes represented in Tables 1, 2, 6, 7, 10, 11, 12, and/or 13, andare preferably selected from Tables 11, 12, and/or 13.

The present invention also provides for a method for determining thebasis for appropriate therapy for a subject diagnosed with true lowbirth weight, comprising: a) identifying one or more true low birthweight associated genes which display differential expression in asubject and are associated with a risk factor; and b) selecting atreatment which offsets the risk factor; wherein offsetting the riskfactor means counteracting the exposures, for example, by providing afactor to which the subject was underexposed, or limiting a factor towhich the subject was overexposed. Optionally, the method may alsoinclude the step of: c) administering the selected (offsetting)treatment.

DEFINITIONS

As used herein, the term “true low birth weight” or “TLBW” refers to acondition where a newborn infant has been identified to haveappropriately increased or decreased expression of a TLBW related geneand/or displays one or more of the following clinical findings, inparticular:

A TLBW infant may exhibit an increase in baseline systolic bloodpressure wherein the increase is characterized by a p-value relative tothe systolic blood pressure in a healthy control infant which is lessthan or equal to 0.1, less than or equal to 0.05, less than or equal to0.01, or less than or equal to 0.001; and/or

A TLBW infant may exhibit an increase in heart rate response duringfeeding that is characterized by a p-value relative to the heart rateresponse during feeding in a healthy control infant which is less thanor equal to 0.1, less than or equal to 0.05, less than or equal to 0.01,or less than or equal to 0.001; and/or

A TLBW infant may exhibit a heart rate increase following a 30° head-uptilt that is characterized by a p-value relative to the heart rateincrease in a healthy control infant following a 30° head-up tilt whichis less than or equal to 0.1, less than or equal to 0.05, less than orequal to 0.01, or less than or equal to 0.001; and/or

A TLBW infant may exhibit a baseline heart rate that is lower than inhealthy control infants wherein the difference in baseline heart rate ischaracterized by a p-value relative to the baseline heart rate in ahealthy subject which is less than or equal to 0.1, less than or equalto 0.05, less than or equal to 0.01, or less than or equal to 0.001;and/or

A TLBW infant may exhibit a decrease in ponderal index, a marker ofthinness in newborn infants, that is characterized by a p-value relativeto the ponderal index in a healthy control infant which is less than orequal to 0.1, less than or equal to 0.05, less than or equal to 0.01, orless than or equal to 0.001.

As a non-limiting example, a TLBW infant may exhibit an increase inbaseline systolic blood pressure of at least 10 mmHG and/or 5 mmHG indiastolic pressure above that of non-TLBW infants.

As a non-limiting example, a TLBW infant may exhibit an increase inheart rate response during feeding that is at least 10 BPM greater thanin non-TLBW infants.

As a non-limiting example, a TLBW infant may exhibit a heart rateincrease that is at least 2 BPM greater than in non-TLBW infantsfollowing a 30° head-up tilt.

As a non-limiting example, a TLBW infant may exhibit a baseline heartrate that is 10 BPM lower than in non-TLBW infants.

As a non-limiting example, a TLBW infant may exhibit a decrease inponderal index, a marker of thinness in newborn infants, that is atleast 5% relative to a healthy control infant.

As used herein, the term “cDNA” can refer to a single-stranded ordouble-stranded DNA molecule. For a single-stranded cDNA molecule, theDNA strand is complementary to the messenger RNA (“mRNA”) transcribedfrom a gene. For a double-stranded cDNA molecule, one DNA strand iscomplementary to the mRNA and the other is complementary to the firstDNA strand.

As used herein, the term “gene” refers to a DNA molecule that eitherdirectly or indirectly encodes a nucleic acid or protein product thathas a defined biological activity. Such genes may also be referred to as“biologically active” genes.

As used herein, two nucleic acid molecules are “functionally equivalent”when they share one or more quantifiable biological function. Forexample, nucleic acid molecules of different primary sequence may encodeidentical polypeptides; such molecules, while distinct, are functionallyequivalent. In this example, these molecules will also share a highdegree of sequence homology. Similarly, nucleic acid molecules ofdifferent primary sequence may share activity as a promoter of RNAtranscription, wherein said RNA transcription occurs in a specificsubpopulation of cells, and responds to a unique group of regulatorysubstances; such nucleic acid molecules are also functionallyequivalent.

As used herein, two nucleic acid molecules are “homologous” when atleast about 60% to 75%, at least about 80%, at least about 90%, at leastabout 95%, or at least about 100% of the corresponding nucleotidescomprising the nucleic acid molecule are identical over a defined lengthof the molecule, as determined using standard sequence analysis softwaresuch as Vector NTI, GCG, or BLAST. DNA sequences that are homologous maybe identified by hybridization under stringent conditions, as definedfor the particular system. Defining appropriate hybridization conditionsis within the skill of the art. See e.g. Current Protocols in MolecularBiology, Volume I, Ausubel et al., eds. John Wiley:New York N.Y., firstpublished in 1989 but with annual updating, wherein maximumhybridization specificity for DNA samples immobilized on nitrocellulosefilters may be achieved through the use of repeated washings in asolution comprising 0.1-2×SSC (15-30 mM NaCl, 1.5-3 mM sodium citrate,pH 7.0) and 0.1% SDS (sodium dodecylsulfate) at temperatures of 65-68°C. or greater. For DNA samples immobilized on nylon filters, a stringenthybridization washing solution may be comprised of 40 mM NaPO4, pH 7.2,1-2% SDS and 1 mM EDTA. Again, a washing temperature of at least 65-68°C. is recommended, but the optimal temperature required for a trulystringent wash will depend on the length of the nucleic acid probe, itsGC content, the concentration of monovalent cations and the percentageof formamide, if any, that was contained in the hybridization solution(Ausubel et al., supra).

As used herein, the term “nucleic acid molecule” includes both DNA andRNA and, unless otherwise specified, includes both double-stranded andsingle-stranded nucleic acids. Also included are molecules comprisingboth DNA and RNA, either DNA/RNA heteroduplexes, also known as DNA/RNAhybrids, or chimeric molecules containing both DNA and RNA in the samestrand. Nucleic acid molecules of the invention may contain modifiedbases. The present invention provides for nucleic acid molecules in boththe “sense” orientation (i.e. in the same orientation as the codingstrand of the gene) and in the “antisense” orientation (i.e. in anorientation complementary to the coding strand of the gene).

As used in this application, the term “purifying” refers to separationof the target nucleic acid from one or more components of the biologicalsample (e.g., other nucleic acids, proteins, carbohydrates or lipids).Preferably, a purifying step removes at least about 50%, more preferablyabout 70% or more, and even more preferably about 90% or more of theother sample components.

As used herein, the term “sequence” refers to a nucleic acid moleculehaving a particular arrangement of nucleotides, or a particularfunction, e.g. a termination sequence.

As used herein, the term “subject” refers to an animal, e.g., a bird ormammal. In one embodiment, the subject is a human. In anotherembodiment, the subject is a newborn infant human or a pregnant humanfemale at term.

As used herein, the term “derived” means “obtained from,” “descendingfrom,” or “produced by.” In the context of tissue or fluid samplesderived from a particular parent source, the term derived refers toobtaining the tissue or fluid samples from the parent source. In thecontext of nucleic acids or polypeptides derived from a particularparent source, the term derived refers to the use of the parent sourceas a template for the nucleic acid sequence or the amino acid sequence.The nucleic acid or polypeptide derived from the parent source maypossess all or part of the nucleic acid or amino acid sequence of theparent source, in the presence or absence of deletions, substitutions,or modification.

As used herein, the term “probe” refers to a nucleic acid oligomer thathybridizes specifically to a nucleic acid target sequence, underconditions that promote hybridization, thereby allowing detection of thetarget sequence. Detection may either be direct (i.e., resulting from aprobe hybridizing directly to the target sequence) or indirect (i.e.,resulting from a probe hybridizing to an intermediate molecularstructure that links the probe and target sequences). The “targetsequence” of a probe refers to a sequence within a nucleic acid,preferably in an amplified nucleic acid, which hybridizes specificallyto at least a portion of a probe oligomer. A probe may hybridize underappropriate hybridization conditions even if not completelycomplementary to the target sequence, if the probe is sufficientlyhomologous to the target sequence.

The probe may be labeled, i.e., joined directly or indirectly to adetectable molecular moiety or a compound that leads to a detectablesignal. Direct labeling can occur through bonds or interactions thatlink the label to the probe, including covalent bonds and non-covalentinteractions (e.g. hydrogen bonding, hydrophobic and ionicinteractions), or formation of chelates or coordination complexes.Indirect labeling occurs through use of a bridging moiety (a “linker”),that joins a label to the probe, and which can amplify a detectablesignal (e.g., see PCT No. WO 95/16055 (Urdea et al.)). Labels are wellknown and include, for example, radionuclides, ligands (e.g., biotin,avidin), enzymes and/or enzyme substrates, reactive groups, redox activemoieties such as transition metals (e.g., Ruthenium), chromophores(e.g., a moiety that imparts a detectable color), luminescent compounds(e.g., bioluminescent, phosphorescent or chemiluminescent labels) andfluorescent compounds. Those skilled in the art will appreciate that alabeled probe may be a mixture of labeled and unlabeled oligonucleotidesthat hybridize specifically to the target sequence, to optimize thespecific activity of the probe reagent for detection.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1. A multiple regression analysis of the use of placental IGF1expression and body length as predictors of heart rate (HR) response tofeeding (x-axis) is compared to the actual measured heart rate (HR)response to feeding (y-axis). Infants were measured for length andplacental IGF1 gene expression, and this information was used to predictthe HR response to feeding (data not shown). The predicted HR responsewas then compared to the actual measured HR response. Length andplacental IGF1 gene expression are both negatively correlated with HRresponse to feeding (rs=0.32, 0.34; ps<0.0-5) and together provide aneven better prediction of HR responses. The predicted HR response tofeeding is an accurate predictor of actual HR response to feeding(Multiple R=0.42, N=59, p=0.004, p<0.005). As IGF1 expression and bodylength both decrease, the HR response is predicted to increase.

FIG. 2. IGF1 expression differs greatly with birth weight although thisrelationship is not linear. IGF1 expression was determined (measuredwith real time PCR as level of fluorescent intensity relative to actin)in babies classified as low birth weight (L), medium birth weight (M),or High birth weight (H). Expression differed greatly between the groupswith L and M having expressing lower levels of IGF1 than H, and Mexpressing IGF1 at levels lower than L.

FIG. 3. True low BW babies with IGF1 expression have larger placentas,but were not thicker nor did they weigh more. Placental diameter wasmeasured in babies classified as having low birth weight. Those babieswith lower levels of IGF1 expression (1) had placental diameters thatwere larger than those babies with higher IGF1 expression levels.

FIG. 4. True low BW babies with low IGF1 expression have higher bloodpressures during the period before feeding. Systolic (gray column) andDiastolic (black column) blood pressure was measured in low birth weightbabies with low IGF1 expression (1) and high IGF1 expression (2) duringthe period before feeding. In both Systolic and Diastolic BP, the lowbirth weight babies with low IGF1 expression had higher levels.

FIG. 5. True low BW babies with low IGF1 expression have greater heartrate (HR) responses to feeding. HR was measured in low birth weightbabies with low IGF1 expression (1) and high IGF1 expression (2) inresponse to feeding. The low birth weight babies with low IGF1expression had HR response to feeding that low birth weight babies withhigher IGF1 expression.

FIG. 6. True low BW babies with low IGF1 expression have greater heartrate (HR) responses to head-up tilting. HR was measured in low birthweight babies with low IGF1 expression (1) and high IGF1 expression (2)in response to head-up tilting. The low birth weight babies with lowIGF1 expression had HR response to feeding that low birth weight babieswith higher IGF1 expression.

FIG. 7. Expression levels in log units of apolipoprotein C-1 (designated“G3”) in the placentas of control rats and those fed high fat diets.

FIG. 8. Expression levels in rat placentas (in log units) of vascularadhesion molecule 1 (designated “G7”) for animals in a 70% caloricreduction during pregnancy group, 50% caloric reduction during pregnancygroup, and a control group.

FIG. 9. Results from rat studies with nutrition manipulations duringpregnancy. Predicted caloric restriction scores (CRS) for the controlgroup, 50% caloric restriction group, 70% caloric restriction group,high fat group, and SSRI treated group. The CRS was calculated assigninga value of 1, 2, or 3 to the gene data from the control, 50% caloricrestriction group, and 70% caloric restriction group, respectively.

FIG. 10. Predicted caloric restriction scores (CRS) for the controlgroup, 50% caloric restriction group, 70% caloric restriction group,high fat group, and SSRI treated group. The CRS was calculated assigninga value of 100, 50, or 30 to the gene data from the control, 50% caloricrestriction group, and 70% caloric restriction group, respectively.

FIG. 11. The relationship between body weight and the prediction scorefor percent normal nutrition is shown. Fetal weight was measured at day21 of gestation, i.e., one day prior to the expected delivery date.

FIG. 12. The mean (±SE) expression values for each of these 6 genes.This figure shows a clear dose-response change in expression associatedwith alcohol exposure during pregnancy.

FIG. 13. The mean estimates of alcohol exposure for each group arecompared to the actual alcohol exposure for each group. Expressionlevels of these genes can be used to produce very accurate estimates ofexposure level.

DETAILED DESCRIPTION OF THE INVENTION Method of Diagnosing True LowBirth Weight

The present invention relates to a method of diagnosing true low birthweight (TLBW) in newborn infants. This method may comprise: (1)measuring the expression of one or more genes associated with true lowbirth weight in an infant subject in a placental sample or a tissuesample collected from the infant; (2) comparing the measured expressionof the TLBW related gene in the sample to the expression level of thesame gene or genes in one or more control samples and/or against astandard value. Gene expression may be measured by any method known inthe art, by measurement of mRNA levels (for example, via microarray orrtPCR) or by measurement of protein levels. Not by way of limitation,the control samples may be from TLBW subjects or normal subjects, andmay be a placental sample or samples derived from another source. Thesample or samples may be analyzed essentially immediately or may bepreserved for later analysis (e.g., frozen, or the RNA may be collectedand stored under standard laboratory conditions). The control samplesmay be derived from subjects with comparable birth weight, e.g., in thesame quintile for birth weight, where a subject is not a TLBW infant.The method may further comprise measurement of a standardized, internalcontrol having constant gene expression, to which relative expression ofthe TLBW related gene may be compared. Appropriate standardized internalcontrols are discussed in more detail below. Alternatively, or inaddition, the characteristic patterns of gene expression in infantsdiagnosed with TLBW associated with various types of fetal exposures maybe embodied in a database or otherwise categorized to provide standardvalues. Such a database may comprise gene expression patterns for bothTLBW infants, and healthy, non-TLBW infants. Standardized values, whichmay be derived from the database, may be displayed in the form of chartsproviding characteristic levels of gene expression. The database, andoutputs from the database, such as charts, may be further categorized byvarious factors, including but not limited to, the subject's birthweight, the subject's gestation time, exposures, as well as othermedical data.

For genes which are downregulated in TLBW infants, a decrease in geneexpression characterized by a p-value relative to gene expression in ahealthy subject which is less than or equal to 0.1, less than or equalto 0.05, less than or equal to 0.01, or less than or equal to 0.001indicates a diagnosis of true low birth weight. As a non-limitingexample, the downregulation may be characterized by a decrease in geneexpression of at least 5 percent, at least 10 percent, at least 20percent, at least 50 percent, or at least 90 percent. Alternatively, forgenes which are upregulated in TLBW infants, an increase in geneexpression characterized by a p-value relative to gene expression in ahealthy subject which is less than or equal to 0.1, less than or equalto 0.05, less than or equal to 0.01, or less than or equal to 0.001indicates a diagnosis of true low birth weight. As a non-limitingexample, the upregulation may be characterized by an increase in geneexpression of at least 5 percent, at least 10 percent, at least 20percent, at least 50 percent, or at least 90 percent.

Threshold values for gene expression for TLBW related genes may bedetermined by measuring the gene expression in healthy, normal non-TLBWinfants. In one embodiment, gene expression in subjects (e.g.,laboratory animals) which have been subjected to restricted nutritionalintake to induce TLBW, for example, caloric restriction (CR), may becompared to the gene expression in comparable subjects with normalnutritional intake, which will be healthy and of normal birth weight,and will not have TLBW. Other nutritional or metabolic factors which maybe varied include, but are not limited to: calories, oxygen, vitamins,minerals, and the appropriate combinations of protein, carbohydrates,and fats. Increases or decreases in gene expression in the TLBW group,relative to the non-TLBW group, indicates a change in gene expressioninduced by TLBW. The level of gene expression in the TLBW group may beused as the threshold value for use in the method of diagnosing TLBW. Itis noted that under- or over-exposure to different nutritional metabolicfactors may result in increase or decrease in different TLBW relatedgenes.

In another embodiment, determination of a threshold value of geneexpression of TLBW related genes may be performed by measuring geneexpression in newborn infants and correlating increases or decreases ingene expression with other TLBW-associated factors, such as changesheart rate, blood pressure, and patterns of postnatal growth. The levelof gene expression for a given gene in an infant which clinicallymanifests TLBW may be used as the threshold value in the method ofdiagnosing TLBW. Based upon the methods described herein, and theexamples provided below, a person of ordinary skill in the art will beenabled to determine threshold values for use in the method of thepresent invention.

In one embodiment, the threshold value of gene expression of a TLBWrelated gene in a healthy subject is the same or similar regardless ofthe birth weight of the subject. The threshold value of gene expressionfor many TLBW related genes does not vary significantly among infants,regardless of birth weight. For these TLBW related genes, the samethreshold value of gene expression may be utilized to measure potentialchanges in gene expression in a subject. A change in gene expression ofa TLBW related gene in a subject which is indicative of TLBW may becharacterized by a p-value relative to the gene expression of the TLBWrelated gene in a healthy subject, which is less than or equal to 0.1,less than or equal to 0.05, less than or equal to 0.01, or less than orequal to 0.001.

In another non-limiting embodiment, the threshold value of geneexpression of a TLBW related gene may vary based upon the birth weightof the subject. Healthy infants born in different quintiles of birthweight may have different threshold levels of expression of TLBW relatedgenes. For example, the threshold gene expression of a TLBW related genein healthy subjects of the lowest quintile (1-20%) may differ from thethreshold gene expression of the same TLBW related gene in healthysubjects in the middle quintile (41-60%) and/or the highest quintile(81-20%). Thus, while the gene expression of a TLBW related gene mayincrease or decrease in infants from one quintile relative to infants ina different quintile, the relative change in TLBW related geneexpression is not necessarily an indication of TLBW. Accordingly, inpreferred but-non-limiting embodiments of the invention, for genes inwhich the level of gene expression may vary by birth weight quintile,the threshold values of TLBW related gene expression which is used maybe determined from healthy subjects of the same birth weight quintile.

The threshold value for a given birth weight quintile may be determinedby measuring the gene expression of a TLBW related gene in infants fromthat birth weight quintile. In one non-limiting embodiment, geneexpression may be measured relative to a standardized, internal controlwhich displays constant gene expression, such as 18S mRNA, GAPDH, oractin. Measurement of gene expression may thus be expressed inlogarithmic (base-10) values relative to the standardized, internalcontrol. A value of log(1) indicates a ten-fold increase in expressionrelative to the standardized, internal control, a value of log(2)indicates a one-hundred-fold increase in expression relative to thestandardized, internal control, and so on. Where the threshold value ofgene expression is expressed as a logarithmic (base-10) value, relativeto a standardized, internal control, the measurement of gene expressionof a particular TLBW related gene must be measured relative to the samestandardized, internal control as well. Because the standardized,internal control is the same, the measured level of gene expression maybe compared as an absolute value against the threshold value of geneexpression.

In one non-limiting embodiment, the threshold level of gene expressionof IGF1, relative to a standardized internal control comprising actin,differs for infants in the lowest birth weight quintile, the mediumbirth weight quintile, and the highest birth weight quintile. FIG. 2shows the baseline gene expression of IGF1 in infants in the threequintiles. As shown in FIG. 2, the threshold gene expression of IGF1relative to actin is about log(1.5) for infants in the lower quintile(1-20 percent) of birth weight. The threshold gene expression of IGF1relative to actin is about log(1) for infants in the middle quintile(41-60 percent) of birth weight. The threshold gene expression of IGF1relative to actin is about log(2) for infants in the upper quintile(81-100 percent) of birth weight. See FIG. 2. These threshold levels ofIGF1 gene expression relative to actin may be used to determine whetherchanges in gene expression in a subject are indicative of TLBW. As oneillustrative example, an IGF1 gene expression value, relative to actin,of log(1.2) would be indicative of TLBW in a subject in the lowestquintile and the highest quintile of birth weight, but would not beindicative of TLBW in a subject in the middle quintile of birth weight.In another example, based upon the threshold values provided above, anIGF1 gene expression value of log(0.1), relative to actin, would beindicative of TLBW in a subject in the lowest, middle, and highestquintiles, as it falls below the threshold values in each category.

Increases or decreases in gene expression are indicative of TLBW if theyare statistically significant, as indicated by the p-values discussedabove. To confirm a diagnosis of TLBW, at least one TLBW-related gene isevaluated, and preferably, the gene expression of additionalTLBW-related genes are concurrently evaluated. The TLBW-related genesevaluated may be utilized as a standard set of genes, wherein the sameset of genes are evaluated between the test subject(s) and the controlsubject(s). The set of genes evaluated may include at least 1TLBW-related gene, at least 2 TLBW-related genes, at least 3TLBW-related genes, at least 4 TLBW-related genes, at least 5TLBW-related genes, at least 6 TLBW-related genes, at least 7TLBW-related genes, at least 8 TLBW-related genes, at least 9TLBW-related genes, at least 10 TLBW-related genes, at least 15TLBW-related genes, at least 20 TLBW-related genes, or at least 25TLBW-related genes.

In a preferred embodiment, the TLBW related genes evaluated include:insulin-like growth factors (“IGF,” e.g., IGF1, IGF2), genes encodingIGF binding proteins (e.g., ALS, CTGF/CCN2, Endocan, IGFBP-1, IGFBP-2,IGFBP-3, IGFBP-4, IGFBP-5, IGFBP-6, IGFBP-7, Nov/CCN3), and genesencoding IGF receptors. TLBW related genes which may be evaluated mayalso be selected from the genes represented in Tables 1, 2, 6, 7, and/or10. Gene expression of a TLBW related gene is decreased in a subjectsample if the decrease in gene expression is characterized by a p-valuerelative to gene expression in a healthy subject which is less than orequal to 0.1, less than or equal to 0.05, less than or equal to 0.01, orless than or equal to 0.001. Gene expression a TLBW related gene isincreased in a subject sample if the increase in gene expression ischaracterized by a p-value relative to gene expression in a healthysubject which is less than or equal to 0.1, less than or equal to 0.05,less than or equal to 0.01, or less than or equal to 0.001.

In a non-limiting embodiment, the TLBW related genes are FAS relatedgenes, and the method of diagnosing TLBW is utilized to diagnose fetalalcohol syndrome. Increases or decreases in gene expression of FASrelated genes are indicative of FAS if they are statisticallysignificant, as indicated by the p-values discussed above. To confirm adiagnosis of FAS, at least one FAS-related gene is evaluated, andpreferably, the gene expression of additional FAS-related genes areconcurrently evaluated. The FAS-related genes evaluated may be utilizedas a standard set of genes, wherein the same set of genes are evaluatedbetween the test subject(s) and the control subject(s). The set of genesevaluated may include at least one FAS-related gene, at least 2FAS-related genes, at least 3 FAS-related genes, at least 4 FAS-relatedgenes, at least 5 FAS-related genes, at least 6 FAS-related genes, atleast 7 FAS-related genes, at least 8 FAS-related genes, at least 9FAS-related genes, at least 10 FAS-related genes, at least 15FAS-related genes, at least 20 FAS-related genes, or at least 25FAS-related genes.

In a preferred embodiment, the FAS-related genes evaluated include:Gusb, Pex6, Arts1, Centa2, Hadhsc, Vps35 (mapped), Tpar1, RGD1305243(predicted), Cdca7, RGD1565289 (predicted), Crsp9 (predicted), Ggps1,Cul2 (predicted), Trp53rk (predicted), Prdm2 (mapped), Ddx59, Mcpt6,Ndufb5 (predicted), Mcts1, Enpp5, MGC72992, Sumf1 (predicted), Plek,Plag1, Rnd3, Inpp1, Zfp207, Akr7a2, Cp, St3gal3, LOC287533, Slc39a4(predicted), Polr3e (predicted), Pcmtd2 (predicted), Kbtbd4 (predicted),Asah1, RGD1564011 (predicted), Mss4, RT1-Aw2, LOC303515, Wig1, Phyh,RGD1308959, Csnk1d, Zfp365, and Lama5. FAS related genes which may beevaluated may also be selected from the genes represented in Tables 1,2, 6, 7, 10, 11, 12, and/or 13, and are preferably selected from Tables11, 12, and 13. Gene expression of a FAS related gene is decreased in asubject sample if the decrease in gene expression is characterized by ap-value relative to gene expression in a healthy subject which is lessthan or equal to 0.1, less than or equal to 0.05, less than or equal to0.01, or less than or equal to 0.001. Gene expression a FAS related geneis increased in a subject sample if the increase in gene expression ischaracterized by a p-value relative to gene expression in a healthysubject which is less than or equal to 0.1, less than or equal to 0.05,less than or equal to 0.01, or less than or equal to 0.001.

Gene expression may be measured from nucleic acids derived from fetaltissue or fluid samples. A preferred tissue sample is placental tissue,which is composed largely of fetal tissue. Preferably, a suitable crosssection is obtained which includes all cell layers, i.e., amnion,chorion, decidua parietalis, endometrial veins and arteries, andmyometrium. Any fetal tissue or fluid sample from a subject may be used.Tissue and fluid samples may be derived from the newborn infant, or frommaternal sources which may contain fetal tissue or fluid. Tissue orfluid samples which may be useful for assaying the expression level ofgenes of interest are any tissues or fluids which may exhibitdifferential gene expression of the target genes. Examples of tissuesamples that may be used include, but are not limited to: placentaltissue, fetal blood, cord tissue, cord blood, amniotic fluid, maternalblood, and endometrium. Tissue and fluid samples may be acquired via anymethod known in the art, including, but not limited to surgicalexcision, aspiration, or biopsy. The tissue and fluid samples may befresh, frozen, or otherwise preserved. In a preferred embodiment,placental tissue is sampled within 48 hours following birth, and placedin a preservative or stabilizer. Examples of preservatives andstabilizers include TRIZOL™ (Invitrogen, Carlsbad, Calif.) and RNALATER™(Ambion, Austin, Tex.).

True Low Birth Weight Associated Genes

As used herein, a “true low birth weight related gene,” “true low birthweight associated gene,” “TLBW-related gene,” or “TLBW-associated gene”refer to a gene which is expressed at a level, in a TLBW infant, whichis different from (increased or decreased) its expression level in anormal, healthy infant. TLBW-related genes may be useful for thediagnosis, treatment, or prevention of true low birth weight, and mayserve as a guide for treatment of the TLBW subject. Genes identified tobe TLBW-related may be used as diagnostic targets for the earlydetection and diagnosis of TLBW, and may be used to differentiatebetween a subject with true low birth weight due to exposure riskfactors such as malnutrition, or a subject which is simply small due toother factors, such as small parents. Genes identified to beTLBW-related may be used to identify exposure to various risk factors,including but not limited to, alcohol abuse, drug abuse, andmalnutrition. For example, the methods of the present invention mayprovide information about nutritional and metabolic deficits andsurfeits during gestation, including but not limited to, calories,oxygen, vitamins, minerals, and the appropriate combinations of protein,carbohydrates, and fats. TLBW-related genes may be targets for genetictherapy or for agents which modulate their expression, for the treatmentor prevention of TLBW.

Differential expression of genes is defined herein as either an increaseor decrease in gene expression, depending on the gene, as compared toexpression in a healthy control subject. Gene expression is consideredincreased when the increase in gene expression is characterized by ap-value which is less than or equal to 0.1, less than or equal to 0.05,less than or equal to 0.01, or less than or equal to 0.001, relative toa comparable sample of a healthy control subject. In non-limitingembodiments, gene expression may be considered increased when the geneexpression is increased by at least 5 percent, at least 20 percent, atleast 50 percent, or at least 90 percent, as compared to the geneexpression in a comparable sample of a healthy control subject. Geneexpression is considered decreased when the decrease in gene expressionis characterized by a p-value which is less than or equal to 0.1, lessthan or equal to 0.05, less than or equal to 0.01, or less than or equalto 0.001, relative to a comparable sample of a healthy control subject.In non-limiting embodiments, the decrease in gene expression may becharacterized by a decrease in gene expression of at least 5 percent, atleast 20 percent, at least 50 percent, or at least 90 percent, ascompared to the gene expression in a comparable sample of a healthycontrol subject.

TLBW-related genes which may be measured according to the methods of thepresent invention may be selected from the genes represented by theprobe sets listed in Table 1, and the human homologs thereof, where theprobe sets are representative of data generated using an Affymetrix RatGenome Chip™ (230.2) (Affymetrix, Santa Clara, Calif.). The genesrepresented by the probe sets listed may be deduced via the NETAFFX™Analysis Center software (Affymetrix, Santa Clara, Calif.) (available atwww.affymetrix.com/analysis/index.affx under the terms and conditionsset forth therein). Table 1 includes data derived from rat experimentsinvolving caloric restriction (CR) of pregnant rats. Table 1 lists probesets which have been identified as having increased expression innewborn rats diagnosed with TLBW (designated by “up”) due to CR, as wellas probe sets which have decreased expression in newborn rats diagnosedwith TLBW (designated “down”) due to CR. Accordingly, measurement of thegenes represented by the probe sets listed in Table 1 will be useful forthe diagnosis of TLBW. Sequence homology between the rat genes and theirhuman equivalents will allow extrapolation of the data of Table 1 foruse in humans and, by analogy, other species.

The present invention also encompasses oligonucleotide sequences whichare complementary to TLBW-related genes. The oligonucleotide sequencesmay be complementary to the genes represented by the probe setsidentified in Table 1. The oligonucleotides may be utilized as primersfor amplification of the TLBW-related genes, for example, by polymerasechain reaction (PCR). The oligonucleotides may also be utilized asprobes for the detection of TLBW-related genes or the measurement ofTLBW-related gene expression. Preparation of primers or probes usingwell-known methods based upon the identified TLBW-related genes will bereadily apparent to those of ordinary skill in the art.

Differential expression of particular TLBW-related genes may beassociated with prenatal exposure to particular risk factors. Deficitsor surfeits of metabolic and nutritional factors are risk factors forTLBW and may cause differential expression of TLBW related genes.Metabolic and nutritional factors include, but are not limited to,calories, oxygen, vitamins, minerals, and the appropriate combinationsof protein, carbohydrates, and fats. Different risk factors maytherefore result in different changes in gene expression for a givenTLBW related gene. Genes which display differential expression which maybe measured according to the methods of the present invention may beselected from the genes represented in Tables 1, 2, 6, 7, 10, 11, 12,and/or 13.

Table 2, based on rat data, sets forth rat genes which show thatexposure to caloric restriction during gestation may cause an increasein a particular TLBW related gene, whereas IUGR may cause a decrease inthe same TLBW related gene. Table 6 sets forth probe sets identifiersfor rat genes (based on an Affymetrix Rat Genome Chip™ (230.2) (seesupra)) which display differential expression due to exposure to a highfat diet during gestation. Table 7 sets forth probe sets identifiers forrat genes (based on an Affymetrix Rat Genome Chip™ (230.2) (see supra))which demonstrate a rank ordered change in expression due to variouslevels of caloric restriction. Table 10 sets forth probe setsidentifiers for rat genes (based on an Affymetrix Rat Genome Chip™(230.2) (see supra)), which display differential expression due toexposure to selective serotonin reuptake inhibitors (SSRIs). Thedifferences in gene expression arising from different exposures duringgestation, such as the differences in gene expression set forth in theforegoing tables, may be utilized to distinguish between exposure todifferent risk factors. The human homologs of the TLBW-related rat genesrepresented by the foregoing tables are encompassed by the invention.Accordingly, the multiple TLBW related genes may be selected andsimultaneously screened to assist in the differentiation of potentialexposure to various risk factors during gestation.

Caloric restriction during gestation may cause differential expressionof a particular set of genes, whereas IUGR caused by other risk factorsmay cause differential expression of different genes. Table 2 identifiesgenes with differential levels of expression in instances of caloricrestriction (CR) and instances of IUGR. This data indicates thatdifferential expression of certain genes may vary based upon caloricrestriction, but do not necessarily correlate with differential geneexpression due to IUGR. As shown in Table 2, various genes are upregulated in both IUGR and CR. These genes include but are not limitedto: proviral integration site 1; homocysteine-inducible, endoplasmicreticulum stress-inducible, ubiquitin-like domain member 1; Protein Creceptor, endothelial (predicted); Solute carrier family 2 (facilitatedglucose transporter), member 2; glycoprotein hormones, alpha subunit;similar to hypothetical protein FLJ13511 (predicted); phospholipaseC-like 2 (predicted); similar to Hypothetical WD-repeat protein CGI-48(predicted); peroxiredoxin 6; Sorting nexin 10 (predicted); leptin;Similar to IER7; Small fragment nuclease (predicted); Tissue factorpathway inhibitor; Similar to IER6; syndecan 1; Jun D proto-oncogene;huntingtin interacting protein 2 (predicted); Ferredoxin 1; solutecarrier family 11 (proton-coupled divalent metal ion transporters),member 2; neuron specific gene family member 1; and Hydroxysteroiddehydrogenase-1, delta<5>-3-beta (predicted).

Table 2 also shows that various genes are down regulated in both IUGRand CR. These genes include but are not limited to: Catalase; colonystimulating factor 1 (macrophage); Zinc finger protein 262 (predicted);immunoglobulin (CD79A) binding protein 1; Hepatocyte growth factor; bonemorphogenetic protein 5 (predicted); adaptor-related protein complex 3,mu 2 subunit; Similar to hypothetical protein FLJ22344 (predicted);Glycine amidinotransferase (L-arginine:glycine amidinotransferase);similar to map kinase interacting kinase; SMC6 structural maintenance ofchromosomes 6-like 1 (yeast) (predicted); aquarius (predicted); sproutyhomolog 2 (Drosophila) (predicted); cytoplasmic FMR1 interacting protein1 (predicted); similar to TBC1 domain family member 4; folate receptor 2(fetal) (predicted); mitogen-activated protein kinase kinase kinasekinase 4 (predicted); Adducin 3 (gamma); FERM domain containing 4B;dystonin (predicted); O-linked N-acetylglucosamine (GlcNAc) transferase(UDP-N-acetylglucosamine:polypeptide-N-acetylglucosaminyl transferase);platelet derived growth factor receptor, beta polypeptide;lysosomal-associated protein transmembrane 4B (predicted); myosin X(predicted); laminin, alpha 2 (predicted); low density lipoproteinreceptor-related protein 6 (predicted); ubiquitin conjugation factor E4A; transforming growth factor beta 1 induced transcript 1; RT1 class I,CE16; RT1 class Ia, locus A2; procollagen, type XV (predicted);protocadherin gamma subfamily C, 3; CD4 antigen; stabilin 1 (predicted);guanylate cyclase 1, soluble, beta 3; Ras homolog gene family, member E;procollagen C-proteinase enhancer protein; peripheral myelin protein 22;fibromodulin; wingless-related MMTV integration site 2; CD44 antigen;intercellular adhesion molecule 2; myeloid cell nuclear differentiationantigen (predicted); complement component 1, r subcomponent (predicted);dihydropyrimidinase-like 3; RT1 class I, CE15; RT1 class Ib, locus Aw2;RT1-149 protein; amine oxidase, copper containing 3; procollagen, typeVI, alpha 3 (predicted); Cytochrome b-245, beta polypeptide; Neuropilin1; caspase 1; Down syndrome critical region homolog 1 (human); Similarto E430002G05Rik protein (predicted); Collagen, type V, alpha 2; Nuclearreceptor subfamily 3, group C, member 1; similar to hypothetical proteinFLJ10652 (predicted); guanylate cyclase 1, soluble, alpha 3; potassiumvoltage-gated channel, delayed-rectifier, subfamily S, member 3;procollagen, type I, alpha 3; insulin-like growth factor 1; allograftinflammatory factor 1; allograft inflammatory factor 2; procollagen,type I, alpha 2; and plasma glutamate carboxypeptidase.

Table 2 also shows that various genes are down regulated in IUGR but areup regulated in CR. These genes include but are not limited to: CUGtriplet repeat, RNA-binding protein 2; aldehyde dehydrogenase family 3,subfamily A2; core-binding factor, runt domain, alpha subunit 2;translocated to, 1; cyclin D-related (predicted); collagen, type V,alpha 3; Nuclear receptor subfamily 2, group F, member 2; ATPase, Ca++transporting, cardiac muscle, slow twitch 2; similar to dJ202D23.2(novel protein similar to C21ORF5 (KIAA0933)) (predicted);Transducin-like enhancer of split 4, E(spl) homolog (Drosophila);Potassium channel, subfamily K, member 3; apurinic/apyrimidinicendonuclease 1; gap junction membrane channel protein alpha 1; ATPase,Ca++transporting, plasma membrane 4; Transducin-like enhancer of split4, E(spl) homolog (Drosophila); Solute carrier family 5 (inositoltransporters), member 3; Klotho; tripartite motif protein 27(predicted); myosin Ib; chromosome condensation 1-like; thymus cellantigen 1, theta; CTD (carboxy-terminal domain, RNA polymerase II,polypeptide A) small phosphatase-like (predicted); cAMP responsiveelement binding protein 1; Ectonucleotidepyrophosphatase/phosphodiesterase 2; LRRC36 homolog (human); Growtharrest specific 6; CDC16 cell division cycle 16 homolog (S. cerevisiae)(predicted); and matrix metallopeptidase 2.

Table 2 also shows that various genes are up regulated in IUGR but aredown regulated in CR. These genes include but are not limited to:Similar to RIKEN cDNA 1500006O09 (predicted); growth differentiationfactor 15; Basic leucine zipper and W2 domains 4; colony stimulatingfactor 2 receptor, beta 1, low-affinity (granulocyte-macrophage);eukaryotic translation termination factor 1 (predicted); similar toRIKEN cDNA 1110012L19; Similar to RIKEN cDNA 3930401K13 (predicted);ubiquitin-conjugating enzyme E2 variant 2; Tankyrase, TRF1-interactingankyrin-related ADP-ribose polymerase 2 (predicted); RAS guanylreleasing protein 1; ornithine decarboxylase antizyme inhibitor;Thymine-DNA glycosylase; microfibrillar-associated protein 3-like(predicted); actin related protein 2/3 complex, subunit 5-like(predicted); polymerase (RNA) II (DNA directed) polypeptide H(predicted); ectonucleoside triphosphate diphosphohydrolase 1;microtubule-associated protein 7 (predicted); Tankyrase,TRF1-interacting ankyrin-related ADP-ribose polymerase 2 (predicted);Similar to methyl-CpG binding protein MBD2; cytochrome P450, family 19,subfamily a, polypeptide 1; hexosaminidase B (predicted); Similar totestis specific protein, Ddc8; Serine/threonine kinase 3; inhibinbeta-A; microfibrillar associated protein 5 (predicted); GULP,engulfment adaptor PTB domain containing 1 (predicted); solute carrierfamily 11 (proton-coupled divalent metal ion transporters), member 3;calpain 6; and Transferrin receptor.

Accordingly, identification of gene expression in various genes mayallow for the diagnosis of CR and IUGR, and may further allow for thedifferentiation of CR from IUGR. In a non-limiting example, increasedexpression of certain genes, such as myosin 1b, or decreased expressionof certain genes, such as growth differentiation factor 15, may beindicative of TLBW due to caloric restriction (CR), but not due to IUGR.See Table 2; see also McMinn et al., supra. Gene expression of certaingenes may allow for the diagnosis of CR or IUGR, but may not be usefulto differentiate between a diagnosis of CR or IUGR. In a non-limitingexample, increases in some genes may be indicative of both IUGR and CR,such as an increase in expression of peroxiredoxin 6. Similarly,decreases in some genes may be indicative of both IUGR and CR, such asan decrease in expression of catalase. To differentiate between IUGR andCR, the gene expression of genes which are up regulated in IUGR but aredown regulated in CR may be measured. Similarly, the gene expression ofgenes which are down regulated in IUGR but are up regulated in CR may bemeasured. In a non-limiting example, a change in expression of myosin 1bmay be used to distinguish between IUGR and CR. Up regulation of myosin1b is indicative of CR, whereas down regulation is indicative of IUGR.This data therefore allows a person of ordinary skill in the art todifferentiate between true low birth weight due to CR and IUGR, and insome cases, may allow identification of the cause of TLBW, such as CR.This further allows selection of an appropriate treatment, for example,increased caloric intake, which is discussed in more detail below. It isunderstood that the human homologs of the TLBW genes represented inTable 2 are encompassed by the present invention.

It will be apparent to a person of ordinary skill in the art that geneexpression data correlated to other risk factors may be utilized todetermine exposure to one or more risk factors. For example, Tables 5and 6 identify probe sets for genes with differential gene expressiondue to exposure to a high fat diet during gestation. Tables 8 and 10identify probe sets for genes with differential expression due toexposure to an SSRI during gestation. Measurement of gene expression ofthe genes represented in Tables 5, 6, 8, and 10 may allow a person ofordinary skill in the art to determine whether a subject has beenexposed to a high fat diet or an SSRI during gestation, based upon theappropriate increase or decrease in gene expression in a gene associatedwith exposure to a high fat diet or an SSRI. This further allowsselection of an appropriate treatment based upon the exposureidentified, as discussed in more detail below. It is understood that thehuman homologs of the TLBW genes listed in Table 5, 6, 8, and 10 areencompassed by the present invention.

Fetal Alcohol Syndrome Related Genes

As used herein, a “fetal alcohol syndrome related gene,” “FAS relatedgene,” “fetal alcohol syndrome associated gene,” and “FAS associatedgene” is a TLBW related gene which is expressed at a level, in an infantwith fetal alcohol syndrome, which is different from (increased ordecreased) its expression level in a normal, healthy infant. FAS relatedgenes may also refer to a TLBW related gene which is expressed at alevel, in an infant with fetal alcohol syndrome, which is different from(increased or decreased) its expression level in an infant with TLBWcaused by exposure to risk factors other than alcohol. FAS-related genesmay be useful for the diagnosis, treatment, or prevention of fetalalcohol syndrome, and may serve as a guide for treatment of the FASsubject. Genes identified to be FAS-related may be used as diagnostictargets for the early detection and diagnosis of FAS, and may be used todifferentiate between a subject with fetal alcohol syndrome or a subjectwith true low birth rate due to other risk factors, such asmalnutrition, or a subject which is simply small due to other factors,such as small parents. For example, the methods of the present inventionmay provide information regarding exposure to alcohol during gestation,including but not limited to, the amount of alcohol exposure and thetime of alcohol exposure. FAS-related genes may be targets for genetictherapy or for agents which modulate their expression, for the treatmentor prevention of FAS.

FAS-related genes which may be measured according to the methods of thepresent invention may be selected from the genes represented by theprobe sets listed in Tables 1, 2, 6, 7, 10, 11, 12, and/or 13,preferably selected from Tables 11, 12, and/or 13, and the humanhomologs thereof, where the probe sets are representative of datagenerated using an Affymetrix Rat Genome Chip™ (230.2) (Affymetrix,Santa Clara, Calif.). The genes represented by the probe sets listed maybe deduced via the NETAFFX™ Analysis Center software (Affymetrix, SantaClara, Calif.) (available at www.affymetrix.com/analysis/index.affxunder the terms and conditions set forth therein). Table 11 includesdata derived from rat experiments involving pregnant rats exposed toalcohol during gestation, and indicates genes identified asdown-regulated due to exposure to alcohol. The genes in the shaded rowsindicate FAS related genes which do not show significant down-regulationdue to exposure during gestation to an SSRI, caloric restriction, orexposure to a high fat diet. Table 12 includes data derived from ratexperiments involving pregnant rats exposed to alcohol during gestation,and indicates genes identified as up-regulated due to exposure toalcohol. The genes in the shaded rows indicate FAS related genes whichdo not show significant up-regulation due to exposure during gestationto an SSRI, caloric restriction, or exposure to a high fat diet.Accordingly, measurement of the genes represented by the probe setslisted in Tables 11 and 12 will be useful for the diagnosis of FAS, andto distinguish FAS related genes from other TLBW related genes which mayshow differential expression due to exposure to risk factors other thanalcohol. Sequence homology between the rat genes and their humanequivalents will allow extrapolation of the data of Tables 11, 12, and13 for use in humans and, by analogy, other species.

The present invention also encompasses oligonucleotide sequences whichare complementary to FAS-related genes. The oligonucleotide sequencesmay be complementary to the genes represented by the probe setsidentified in Tables 1, 2, 6, 7, 10, 11, 12, and/or 13, and arepreferably complementary to the genes represented by the probe setsidentified in Tables 11, 12, and/or 13. The oligonucleotides may beutilized as primers for amplification of the FAS-related genes, forexample, by polymerase chain reaction (PCR). The oligonucleotides mayalso be utilized as probes for the detection of FAS-related genes or themeasurement of FAS-related gene expression. Preparation of primers orprobes using well-known methods based upon the identified FAS-relatedgenes will be readily apparent to those of ordinary skill in the art.

Differential expression of particular FAS-related genes may beassociated with prenatal exposure to alcohol. As discussed above,different risk factors may result in different changes in geneexpression for a given TLBW related gene. Accordingly, identification ofdifferential expression in an FAS related gene but not in an TLBWrelated gene provides a useful method of differentiating prenatalexposure to alcohol from prenatal exposure to other risk factors.Similarly, identification of differential expression of an FAS gene inaddition to the identification of differential expression of a differentTLBW related gene provides information regarding specific prenatalexposure to alcohol, in addition to potential exposures to other riskfactors. Genes which display differential expression which may bemeasured according to the methods of the present invention may beselected from the genes represented in Tables 1, 2, 6, 7, 10, 11, 12,and/or 13.

As discussed in more detail above, Tables 1, 2, 6, 7, 10, 11, 12, and 13set forth probe sets identifiers for rat genes (based on an AffymetrixRat Genome Chip™ (230.2) (see supra)), which display differentialexpression due to exposure to caloric restriction, exposure to a highfat diet, exposure to selective serotonin reuptake inhibitors (SSRIs),and exposure to alcohol. The differences in gene expression arising fromdifferent exposures during gestation, such as the differences in geneexpression set forth in the foregoing tables, may be utilized todistinguish between exposure to different risk factors. It will beapparent to a person of ordinary skill in the art that gene expressiondata correlated to other risk factors may be utilized to determineexposure to one or more risk factors. The human homologs of theTLBW-related or FAS related rat genes represented by the foregoingtables are encompassed by the invention. Accordingly, the multiple TLBWrelated and/or FAS related genes may be selected and simultaneouslyscreened to assist in the differentiation of potential exposure tovarious risk factors during gestation.

Measurement of TLBW Related Gene Expression

The following description of the measurement of TLBW related geneexpression is intended as an example, and is non-limiting. The describedmethods of measuring TLBW related genes may be utilized to measure TLBWrelated gene expression due to a variety of exposures, including but notlimited exposure to alcohol. A tissue sample is obtained from thesubject, preferably immediately following birth, within one hourfollowing birth, within 24 hours following birth, or within 48 hoursfollowing birth. The present invention further encompasses a tissuesample obtained in utero, for example, a placental biopsy performedpre-delivery. Preferably, the tissue sample is placental tissue (whichhas been maintained in a condition to protect the integrity of theplacental RNA), which is excised from the portion of the placenta fromwhich the umbilical cord protrudes. RNA is extracted from the tissuesample immediately where possible. If RNA cannot be extracted until alater time, the tissue sample is placed in a suitable stabilizer orpreservative. An example of a suitable stabilizer is RNALATER™. RNA ispreferably extracted by the guanidine thiocyanate method. An example ofa reagent which may be utilized in the guanidine thiocyanate method isTRIZOL™.

RNA which has been purified utilizing the methods described above may beamplified using any nucleic acid amplification assay utilized fordetection of low numbers of RNA molecules. RNA may be amplifiedutilizing primers directed to the TLBW related genes, which allows formeasurement of the relative expression of the TLBW related gene.Preferably, methods of RNA amplification which preserve the relativecomposition of the RNA are utilized. In a preferred embodiment, nucleicacids may be detected by utilizing quantitative polymerase chainreaction (PCR). Quantitative PCR allows for the accurate measurement ofthe relative amount of RNA transcripts present in a sample, whichcorrelates with the relative level of gene expression. For example,quantitative PCR utilizing primers directed to IGF1 may be used.Amplification and detection of the expression of the IGF1 gene may beperformed in both a test sample (a sample derived from the subject beingtested for TLBW) and a control sample (a sample derived from a subjectof known gene expression, such as a healthy, non-TLBW infant). Astandardized, internal control sample which has constant gene expressionmay also be used as a reference for normalization of gene expression.Suitable standardized, internal controls will be known to those ofordinary skill in the art, and include, but are not limited to, 18SmRNA, GAPDH, and actin. Gene expression may be expressed as a base-10logarithmic increase relative to the standardized, internal controlsample. For example, a value of log(1) indicates a 10-fold greaterexpression than the internal control sample. Any methods known in theart for amplifying RNA may be utilized, and include, but are not limitedto: reverse transcriptase polymerase chain reaction, ligase chainreaction, branched DNA signal amplification, amplifiable RNA reporters,Q-beta replication, transcription-based amplification, boomerang DNAamplification, strand displacement activation, cycling probe technology,isothermal nucleic acid sequence based amplification, and otherself-sustained sequence replication assays. See Sambrook, supra.

In another embodiment, nucleic acids may be detected by hybridizationwith a complementary sequence, such as an oligonucleotide probe. SeeU.S. Pat. No. 5,503,980 (Cantor), U.S. Pat. No. 5,202,231 (Drmanac etal.), U.S. Pat. No. 5,149,625 (Church et al.), U.S. Pat. No. 5,112,736(Caldwell et al.), U.S. Pat. No. 5,068,176 (Vijg et al.), and U.S. Pat.No. 5,002,867 (Macevicz). Methods of detecting gene expression viahybridization with oligonucleotide probes include northern blots,phosphorimaging, southern blots, and dot blots. See Sambrook, supra. Ina non-limiting example, detection may be performed utilizing an array ofoligonucleotide probes assembled on a chip, referred to as a DNA chip ora DNA microarray, may be used to detect nucleic acids by hybridization.See U.S. Pat. Nos. 5,837,832 and 5,861,242 (Chee et al.). An example ofa DNA chip is the GENECHIP™, available from Affymetrix (Santa Clara,Calif.). The DNA chip may contain oligonucleotide probes which arehomologous to known genetic sequences, and are used to identify specificgenes. Nucleic acids isolated from the tissue and fluid samples willhybridize to complementary sequences on the DNA chip, and the resultingDNA chip may be analyzed to determine which oligonucleotide probes havebeen hybridized. Analysis of the DNA chip may be performed bybiotinylating the nucleic acids isolated from the tissue and fluidsamples; once the nucleic acids are hybridized to the DNA chip,streptavidin coupled to a fluorescent dye may be added. Alternatively,streptavidin may be added, followed by staining with ananti-streptavidin antibody. The anti-streptavidin antibody may beconjugated to a fluorescent dye, or may be bound by an additionalantibody which is conjugated to a fluorescent dye. The resultingfluorescence-stained DNA chip may be scanned with a confocal laser,which causes the fluorescent dye to fluoresce. The resultingfluorescence pattern may be used to determine which oligonucleotideprobes have been hybridized. In a preferred embodiment, GENECHIPs™ maybe used to determine expression.

Labeled probes may be utilized to detect a nucleic acid. If a labeledprobe hybridizes to the isolated nucleic acid, the label is preferablyone that can be detected in a homogeneous system (i.e., one that doesnot require unbound probe to be separated from the isolated nucleic acidhybridized to probe for detection of bound probes). Alternatively,isolated nucleic acids or fragments thereof may be hybridized to anarray of probes as on a DNA chip and those probes that specificallyhybridize to the isolated nucleic acids are detected to provide sequenceinformation about the isolated nucleic acids. Those skilled in the artwill appreciate that more than one procedure may be used to detect theisolated nucleic acids.

Kits for Diagnosing True Low Birth Weight

The present invention further provides kits for diagnosing true lowbirth weight in a subject. The methods, PCR primers, and nucleotidesequences described herein may be efficiently utilized in the assemblyof a diagnostic kit, which may be used to diagnose TLBW in a subject.The kit is useful in distinguishing between newborn infants sufferingfrom TLBW due to the presence of the risk factors identified above andnormal, healthy newborn infants which are simply small. Such adiagnostic kit contains the components necessary to practice the methodsas described above.

Thus, the kit may contain a sufficient amount of at least one probecomplementary to an TLBW-related gene. The kit may also contain asufficient amount of at least one PCR primer pair for an TLBW-relatedgene, for the amplification of the TLBW-related gene or detection of theTLBW-related gene. In a preferred embodiment, the primer pair is usedfor the detection of the TLBW-related gene utilizing RT-PCR. The kit mayoptionally comprise reagents and instruments necessary for thecollection of samples. The kit may optionally comprise components of adetectable labeling system, vials for containing the tissue or fluidsamples, substrates for the preservation of tissue or fluid samples,control tissue or fluid samples (e.g., dried or frozen tissue or fluidfrom a healthy fetus, newborn infant, or mother), protein samples, andthe like. Control reagents may comprise healthy tissue samples, ortissue or fluid samples which have known expression levels forparticular genes. Control samples may be included for one or more birthweight quintiles. A reference standard, comprising nucleic acid at aconcentration that would be found in a control sample, may also beprovided. An internal control sample, for example, actin, may also beincluded. The control reagents may be fresh, frozen, or otherwisepreserved. The kit may also include a means for extracting the tissue orfluid samples. The kit may also provide reagents and materials forpreserving the tissue or fluid samples. Other conventional components ofsuch diagnostic kits may also be included. In a preferred embodiment,the oligonucleotide probes comprise sequences complementary to portionsof genes encoding an insulin-like growth factor (“IGF,” e.g., IGF1,IGF2), or a gene related to IGF, including but not limited to, genesencoding IGF binding proteins (e.g., ALS, CTGF/CCN2, Endocan, IGFBP-1,IGFBP-2, IGFBP-3, IGFBP-4, IGFBP-5, IGFBP-6, IGFBP-7, Nov/CCN3), andgenes encoding IGF receptors. The kits may also comprise oligonucleotideprobes comprising sequences complementary to portions of the genesrepresented in Tables 1, 2, 6, 7, 10, 11, 12, and 13. In specificnon-limiting embodiments, the oligonucleotides may be a primer pair foruse in PCR. In a preferred embodiment, the kit contains oligonucleotideprobes directed to more than one TLBW-related genes. Oligonucleotideprobes representing TLBW-related genes may be mounted on a substrate,such as a gene chip.

The kit may contain a sufficient amount of at least one probecomplementary to an FAS-related gene. The kit may also contain asufficient amount of at least one PCR primer pair for an FAS-relatedgene, for the amplification of the FAS-related gene or detection of theFAS-related gene. In a preferred embodiment, the primer pair is used forthe detection of the FAS-related gene utilizing RT-PCR. The kit mayoptionally comprise reagents and instruments necessary for thecollection of samples. The kit may optionally comprise components of adetectable labeling system, vials for containing the tissue or fluidsamples, substrates for the preservation of tissue or fluid samples,control tissue or fluid samples (e.g., dried or frozen tissue or fluidfrom a healthy fetus, newborn infant, or mother), protein samples, andthe like. Control reagents may comprise healthy tissue samples, ortissue or fluid samples which have known expression levels forparticular genes. Control samples may be included for one or more birthweight quintiles. A reference standard, comprising nucleic acid at aconcentration that would be found in a control sample, may also beprovided. An internal control sample, for example, actin, may also beincluded. The control reagents may be fresh, frozen, or otherwisepreserved. The kit may also include a means for extracting the tissue orfluid samples. The kit may also provide reagents and materials forpreserving the tissue or fluid samples. Other conventional components ofsuch diagnostic kits may also be included. In a preferred embodiment,the oligonucleotide probes comprise sequences complementary to portionsof the following genes: Gusb, Pex6, Arts1, Centa2, Hadhsc, Vps35(mapped), Tpar1, RGD1305243 (predicted), Cdca7, RGD1565289 (predicted),Crsp9 (predicted), Ggps1, Cul2 (predicted), Trp53rk (predicted), Prdm2(mapped), Ddx59, Mcpt6, Ndufb5 (predicted), Mcts1, Enpp5, MGC72992,Sumf1 (predicted), Plek, Plag1, Rnd3, Inpp1, Zfp207, Akr7a2, Cp,St3gal3, LOC287533, Slc39a4 (predicted), Polr3e (predicted), Pcmtd2(predicted), Kbtbd4 (predicted), Asah1, RGD1564011 (predicted), Mss4,RT1-Aw2, LOC303515, Wig1, Phyh, RGD1308959, Csnk1d, Zfp365, and Lama5.The kits may also comprise oligonucleotide probes comprising sequencescomplementary to portions of the genes represented in Tables 1, 2, 6, 7,10, 11, 12, and 13. In specific non-limiting embodiments, theoligonucleotides may be a primer pair for use in PCR. In a preferredembodiment, the kit contains oligonucleotide probes directed to morethan one FAS-related genes. Oligonucleotide probes representingFAS-related genes may be mounted on a substrate, such as a gene chip.

The diagnostic kits may also include instructions for using the includedcomponents. The kit may also include computer software to aid in themeasurement of gene expression or the calculation of expression ratios.The kit may include or provide access to a database comprisingcharacteristic gene expression information, allowing for the levels ofmeasured gene expression to be compared to a set of standardized data.The kit may include information regarding characteristic gene expressionratios, for example, in the form of charts.

The kits may include a means for extracting tissue or fluid samples.Preferably, the means will be capable of extracting a cross-section ofthe tissue which captures all cell layers in the target sample. The kitsmay optionally comprise reagents for preserving RNA or DNA in a tissueor fluid sample. The kits may additionally comprise reagents andequipment for purifying nucleic acids from tissue or fluid samples,which may include any reagents or equipment known to persons of ordinaryskill in the art for purification of nucleic acids. Reagents andequipment for measuring gene expression may include any reagents orequipment known to persons of ordinary skill in the art for detectinggene expression.

Intervention and Treatment of True Low Birth Weight

The present invention further relates to methods for treating infantsdiagnosed with true low birth weight utilizing the methods of thepresent invention. As noted above, differential expression of particulargenes may be associated with exposure to particular risk factors. Thepresent invention thus provides for a method of identifying theexposures of the infant subject, and further provides for identificationof appropriate treatments to offset the deleterious effects of theexposures. As used herein, the term “exposures” refers to exposure offetuses to the risk factors detailed above, and may refer toover-exposure or under-exposure to the risk factors. For example,exposures may refer to deficits and surfeits during gestation ofcalories, oxygen, vitamins, minerals, and the appropriate combinationsof protein, carbohydrates, and fats.

Exposure to risk factors may be correlated to gene expression bymeasuring the changes in gene expression in genes that are associatedwith the risk factors. Determination of which genes are associated witha particular risk factor may be performed by measuring the geneexpression in subjects which have been exposed to the risk factor, andcomparing the measured gene expression to the gene expression of thesame gene in a healthy subject. Where gene expression of a particulargene in the subject exposed to a risk factor exhibits a statisticallysignificant change relative to gene expression in the healthy subject,then changes in expression of the gene may be correlated to the riskfactor. Examples of genes correlated to various risk factors areprovided below. Measurement of gene expression may be conducted inlaboratory animals, such as mice or rats, which have been exposed to arisk factor. It will be known to a person of ordinary skill in the artthat sequence homology between the rat genes and the human equivalentswill allow extrapolation of this data for use in other species, such ashumans. The measurement of gene expression may also be made in humansubjects at the time of birth, and exposure to risk factors duringgestation may be identified via examination of the mother's relevantmedical records.

In non-limiting embodiments, gene expression may be measured in subjectswhich have been exposed to caloric restriction, a high fat diet, orSSRIs. In a non-limiting example, Table 1 provides a list of genes whichexhibit changes in expression where the fetus was exposed to caloricrestriction (CR). Table 2 also provides a list of genes which exhibitchanges in expression where the fetus was exposed to CR duringgestation, and which also suffers from IUGR. Accordingly, measurement ofchanges in gene expression of the genes represented in Table 1 or Table2 may allow a person of ordinary skill in the art to determine if afetus has been exposed to CR during gestation and/or suffers from IUGR.Distinguishing between CR and IUGR is discussed in greater detail above.

In another non-limiting example, Table 6 provides a list of probe setsrepresentative of rat genes which exhibit changes in expression when thefetus is exposed to a high fat diet during gestation. Accordingly,measurement of changes in gene expression of the genes represented inTable 6 and their human homologs may allow a person of ordinary skill inthe art to determine if a fetus has been exposed to a high fat dietduring gestation. The genes represented by Table 6 indicate a decreasein gene expression where the gene expression in subjects with a high fatdiet (designated by “HF”) is decreased relative to the gene expressionof the control subjects (designated “Cont”). The genes represented byTable 6 indicate an increase in gene expression where the geneexpression in subjects with a high fat diet (designated by “HF”) isincreased relative to the gene expression of the control subjects(designated “Cont”). Based upon this information, a person of ordinaryskill in the art will be capable of identifying exposure to a high fatdiet based upon an increase or decrease in expression of one or moregenes represented by Table 6.

In another non-limiting example Table 10 provides a list of probe setsrepresenting genes which exhibit changes in expression when the fetus isexposed to a selective serotonin reuptake inhibitor (SSRI) duringgestation. Accordingly, measurement of changes in gene expression of thegenes represented in Table 10 may allow a person of ordinary skill inthe art to determine if a fetus has been exposed to SSRIs duringgestation. The genes represented by Table 10 indicate a decrease in geneexpression where the gene expression in subjects exposed to an SSRI(designated by “SSRI”) is decreased relative to the gene expression ofthe control subjects (designated “C”). The genes represented by Table 10indicate an increase in gene expression where the gene expression insubjects exposed to an SSRI (designated by “SSRI”) is increased relativeto the gene expression of the control subjects (designated “C”). Basedupon this information, a person of ordinary skill in the art will becapable of identifying exposure to an SSRI based upon an increase ordecrease in expression of one or more genes represented by Table 10.

In another non-limiting example Tables 11, 12, and 13 provide lists ofprobe sets representing genes which exhibit changes in expression whenthe fetus is exposed to alcohol during gestation. Accordingly,measurement of changes in gene expression of the genes represented inTables 11, 12, and/or 13 may allow a person of ordinary skill in the artto determine if a fetus has been exposed to alcohol during gestation.The genes represented by Tables 11 indicate a decrease in geneexpression where the gene expression in subjects exposed to alcohol isdecreased relative to the gene expression of control subjects. The genesrepresented by Table 12 indicate an increase in gene expression wherethe gene expression in subjects exposed to alcohol is increased relativeto the gene expression of control. Based upon this information, a personof ordinary skill in the art will be capable of identifying exposure toalcohol based upon an increase or decrease in expression of one or moregenes represented by Tables 11, 12, and/or 13.

It is envisioned that methods of treatment of infants diagnosed withtrue low birth weight or which have been diagnosed to have been exposedto one or more risk factors will be tailored to the infant dependingupon the TLBW-related gene identified. The treatment is optimallyselected to offset the exposures experienced by the newborn infant. Asused herein, the term “offset” means counteracting the exposures. Itwill be within the ability of those skilled in the art to identify andselect an appropriate treatment, such as a modified diet oradministration of a dietary supplement, which will offset exposure tothe risk factor. In a non-limiting example, expression of anTLBW-related gene associated with a deficit or surfeit of one or morenutrients, including but not limited to vitamins, minerals, protein,carbohydrates, and fats, may indicate the necessity to administer anutrient-enriched formula to offset the exposure. For example, poorprotein consumption during gestation may indicate the necessity foradministration of a protein-enriched formula, or a change in expressionof an TLBW-related gene associated with carbohydrate overfeeding mayalso indicate the necessity for administration of a carbohydrate-reducedformula. Selection and administration of the appropriate treatment tooffset exposure to a risk factor will be apparent to those of ordinaryskill in the art. Such treatment may include administration of dietswith increased or reduced nutrient intake, based upon the exposureidentified. The treatment may also include administration of diets withappropriately balanced level of nutrients, such as vitamins, minerals,proteins, carbohydrates, and fats. The treatment may also includeadministration of agents drugs or other supplements, which may assist inthe uptake of nutrients or may counteract the effects of the exposures.

In a non-limiting example, an identification of differential expressionof an TLBW-related gene associated with caloric restriction may indicatethe necessity for administration of an enriched formula and/or anincrease in caloric intake. Examples of genes which may be measured todetermine if the subject has been exposed to caloric restriction can befound in the genes represented by the probe sets listed in Table 1 andthe genes listed in Table 2, and their human homologs. Furthermore, asdiscussed in more detail above, the list of genes represented in Table 2may be used to determine whether a subject has been exposed to caloricrestriction and/or which suffers from IUGR. Where a TLBW generepresented in Tables 1 or 2 (including human homologs) has beenidentified as appropriately increased or decreased in a subject, themethod of treatment will be apparent to a person of ordinary skill inthe art. For example, the subject may be administered an diet withincreased caloric intake, or the subject may be administered dietarysupplements.

In another non-limiting example, an identification of differentialexpression of an TLBW-related gene associated with exposure to a highfat diet during gestation may indicate the necessity for administrationof a nutrient-enriched formula and/or reduced fat diet. Examples ofgenes which may be measured to determine if the subject has been exposedto a high fat diet during gestation can be selected from the genesrepresented by probe sets listed in Table 6. Where a TLBW gene fromTable 6 has been identified as appropriately increased or decreased in asubject, the method of treatment will be apparent to a person ofordinary skill in the art. For example, the subject may be administereda diet with reduced fat, or the subject may be administered a dietcontaining the appropriately balanced level of nutrients.

The methods described herein may be used to identify exposure tonon-dietary risk factors such as tobacco, alcohol, and drug abuse. Forexample, Table 10 provides a list of probe sets representing genes whichexhibit a change in expression where the subject is exposed to aselective serotonin reuptake inhibitor (SSRI). Where a TLBW generepresented by Table 10 has been identified as appropriately increasedor decreased in a subject, the method of treatment will be apparent to aperson of ordinary skill in the art. For example, the subject may beadministered an enriched-diet, or administered agents which maycounteract the effects of the SSRIs.

Statistical Analysis

Genetic screening data obtained utilizing the methods described abovemay be analyzed via well known statistical methods. Any method ofstatistical analysis which is well known in the art may be utilized inthe present invention. Computer software may be utilized to perform thestatistical analysis. An example of computer software which may be usedin the present invention is SYSTAT™ (Systat Software, Inc., PointRichmond, Calif.).

As a non-limiting example, ANOVA (analysis of variations) may beutilized to analyze data sets. The analysis may be corrected formultiple comparisons, utilizing, for example, the Benjamini-Hochbergcorrection. Utilizing statistical analysis techniques to compare data, at-test may be performed to compare the subject sample to the controlsample and to determine if differences in value are due to randomfluctuations or are due to other contributing factors. Differences invalue represent increases or decreases in gene expression, and whetherthey are due to random fluctuations or other contributing factors willdepend upon the p-value derived. A p-value may be derived from thet-test results, and is a measure of the probability that increases ordecreases in gene expression are due to random variations. Thus, alarger p-value indicates a greater likelihood that increases ordecreases are most likely due to random variation. Conversely, a smallerp-value indicates that increases or decreases are less likely to berandom, and are caused by another contributing factor, such as geneticdysregulation due to dietary restrictions. As used herein, an increaseor decrease in gene expression is “statistically significant” if thep-value for the increase or decrease, relative to gene expression in ahealthy subject, is less than or equal to 0.1, less than or equal to0.05, less than or equal to 0.01, or less than or equal to 0.001.

As another non-limiting example, discriminant analysis may also beutilized to analyze the data sets. Discriminant analysis may be used todetermine if any identified variables discriminate between two or morenaturally occurring groups. For example, expression of a particular genein a given group may be reduced relative to the control group, may bethe same as the control group, or may be increased relative to thecontrol group. Therefore, discriminant analysis may be used to determinewhich group a particular gene falls into, based upon its measured levelof expression. Discriminant analysis may be performed to determine whatvariables may be used as a predictor of gene expression. Methods ofperforming discriminant analysis are well known in the art, and will bewithin the knowledge and capabilities of persons of ordinary skill inthe art.

In another non-limiting example, linear regression may also be utilizedto analyze the data sets. Linear regression may be used to determinewhether two variables are related, and to what degree, by fitting alinear equation to the observed data. Methods of performing linearregression are well known in the art, and will be within the knowledgeand capabilities of persons of ordinary skill in the art.

Other methods of statistical analysis are well known in the art, and mayalso be performed by those of ordinary skill in the art.

The following nonlimiting examples serve to further illustrate thepresent invention.

EXAMPLES Example 1

Epidemiological studies indicate that babies born in the lower extremeof birth weight (BW) are at risk for physical and mental diseases inadulthood. Heart rate (HR) and blood pressure (BP) responses to feedingwere measured within the first days of life in order to determinewhether signs or markers of this increased vulnerability could bedetected early in life. Preliminary studies indicate that term babieswith low BWs had the greatest increases in HR during feeding. Placentagene expression markers associated with fetal growth were examined todetermine if they may be related to these physiological responses.

To briefly summarize, 33 term infants, enrolled to include a broad rangeof BWs, were bottle-fed a sweetened solution of 5% dextrose for 5minutes. HR and BP changes were measured as values during feeding minusvalues during baseline just before feeding. Placenta samples were takenshortly after delivery and expression of Insulin-like Growth Factor I(IGF1) was measured using quantitative real-time PCR.

Gene expression in newborn human infants was tested in conjunction withidentification of physiologic correlates of birth weight. Heart rate andblood pressure differences was measured between term infants with birthweights on the low end of the normal distribution versus those withaverage or high birth weights. Placental gene expression of IGF1 wasassessed to determine if infants could be identified which might be atgreatest risk.

Subjects

Healthy, full-term infants that were in the low, middle, or highquintiles of birth weight were enrolled for these studies. Infants wereexcluded from the study if one of the following factors was present:evidence of drug abuse, congenital anomalies, APGAR (Activity PulseGrimace Appearance Respiration) scores less than 7 at one or fiveminutes, admission to the neonatal intensive care unit, and gestationalages less than 38 or greater than 41 weeks.

Newborn infants were tested in the hospital prior to discharge atbetween 12 and 98 hours of age. Testing was done during regularlyscheduled feedings between 09:00 and 15:00. Bottle feeding infants werefed either sweetened water (D5W) or formula by a research assistant.Prior to feeding, a cuff of appropriate size for newborns (4-5 cm) wasplaced on the infant's leg below the knee for measurement of bloodpressure. Blood pressure and heart rate measurements were made using aDinamap clinical monitor.

Physiological measurements were made a few minutes before feeding whilebeing held in the supine position by the feeder, during the first 5minutes of feeding, and again after feeding was completed. During eachperiod, a series of five blood pressure measurements was made, eachseparated by about one minute. At the end of the first five minutes offeeding the volume of nutrient consumed is noted, and the babies werethen allowed to complete the feeding.

After feeding, babies underwent a series of tilt challenges involvingfour tilts, twice to a 30° head-up position and twice to a 30° head-downposition. Babies were held in each position for 90 seconds.

IGF1 Gene Expression

Placentas samples were collected 24-36 hours after delivery. Sampleswere dissected in a consistent manner so that each sample had the samepart of the placenta. Dissections were done at a quick pace on top of apetri-dish containing cold RNAlater. Using a dissecting razor, centersections of the placenta were taken (‘center’ meaning the portion of theplacenta from which the umbilical vein protruded). The portion was cutthrough all cell layers (Amnion, Chorion, Decidua Parietalis,Endometrial veins and arteries and Myometrium) so as to include allsections of the placenta and ensure a complete look into the geneticmakeup of the tissue. Dissected tissue were stored in 200 μl of TRIZOL™.Total RNA was extracted using the guanidine thiocyanate method (usingthe TRIZOL™ reagent; Invitrogen, Carlsbad, Calif.).

Small PCR products (<100 base-pairs) were amplified in quadruplets on anOpticon real-time PCR machine (MJ Research, Waltham, Mass.), usinguniversal PCR conditions (65° C. to 59° C. touch-down, followed by 35cycles [15 minutes at 95 C, 10 minutes at 59 C and 10 minutes at 72 C]),as described previously (Galfalvy et al. BMC Bioinformatics, 2003,4:37). 150 pg of cDNA was amplified in 20 μl reactions [0.3× Sybr-green,3 mM MgCl₂, 200 μM dNTPs, 200 μM primers, 0.5 unit Platinum Taq DNApolymerase (Invitrogen, Carlsbad, Calif.)]. Primer-dimers were assessedby amplifying primers without cDNA. Primers were retained if theyproduced no primer-dimers or non-specific signal only after 35 cycles.Results were calculated as relative intensity compared to actin. Thelast cycle was retained as baseline for comparison with “absent” genes.To limit the effect of putative RNA degradation on PCR amplification,primers were designed in the extreme 3′ end of the gene transcript andgene-specific cDNAs were produced for each samples using gene-specificreverse primers during the reverse transcription reaction (Sibille etal. J. Neuroscience, 2000, 20(8)2758-65).

Results

Multiple regression analyses that included IGF1 expression, gestationalage, birth weight, length, and head, abdomen and chest circumferencesshowed that length and IGF1 expression were the best predictors of HRresponses to feeding. Each measure showed a negative correlation with HRreactivity and together had a multiple R of 0.623, p<0.002. Using thesetwo variables, we could identify 10 of the 11 infants with HR responsesthat were greater than 20 BPM. These results suggest that physical andgene expression markers of fetal growth provide good predictors ofinfant physiology and, perhaps markers of later cardiovascular diseasevulnerability.

Measurement of placental IGF1 expression levels in these babies showsthat IGF1 varies across body weight classifications, with the heaviestbaby class having the highest level of IGF1 expression (FIG. 2). Inaddition to IGF1 expression levels, TLBW babies also show variation incardiovascular function such as HR and blood pressure (BP) response tofeeding. This data therefore shows that IGF1 expression may be used as areliable and objective method for diagnosing TLBW.

Example 2 Test of Expression Profile Sensitivity and Specificity Methods

Gene expression data from pregnant rats under different forms of dietaryrestriction was gathered. Five groups of rats were fed different dietsor administered fluoxetine as follows:

-   -   Group 1 (Controls): Rats with ad libitum food through out        pregnancy. (N=8)    -   Group 2 (CR50): Rats Given 50% of their Normal Daily Intake of        Food. (N=5)    -   Group 3 (CR70): Rats Given 70% of their Normal Daily Intake of        Food. (N=5)    -   Group 4 (HF): Rats Given a High Fat (45% Animal Fat)/High Energy        (4.73 kcal/g) diet throughout gestation. (N=6)    -   Group 5 (SSRI): Rats give Fluoxetine (˜10 mg/kg/day) throughout        gestation. (N=6)        Placentas from the rats of each Group were harvested on Day 21        of gestation. RNA was extracted and gene expression was measured        based on hybridization of RNA to Affymetrix Rat Genome Chips™        (230.2) (Affymetrix, Santa Clara, Calif.).

Results Discrimination of High Fat Diet

Probe sets which showed a significant difference between Control and HFgroups were first identified. When utilizing Benjamini adjusted p valueswhere p<0.05 was used as the cut-off, 6,939 probe sets were identifiedwhich exhibited altered expression based on the high fat diet. Whenutilizing Benjamini adjusted p values where p<0.001 was the cutoff, 386probe sets were identified. The entire list of the 386 probe setsidentified are attached as Table 6. From the 386 probe sets identified,5 genes were chosen to include in the analysis. The 5 genes are shownbelow in Table 5. There was no systematic basis for this selection otherthan the probe set had an identified gene name. Any set of genes whichexhibit a significant change in gene expression due to dietaryrestriction may be used.

TABLE 5 PROBE SET NAME FUNCTION 1369179 peroxisome proliferationadipocyte differentiation activated receptor (gamma) 1368271 fatty acidbinding protein 4 lipid binding 1368587 apolipoprotein C-1 lipidtransport activity 1387027 lectin, galactose binding ion transport,sugar binding, soluble 9 binding 1387663 glia maturation factor betacell growth

FIG. 7 shows the expression levels (log units) for the control group(group 3) and the HF group (group 4) for apolipoprotein C-1 (probe set1368587) (designated “G3”).

Discrimination of Caloric Restriction

Utilizing ANOVA analysis, Affymetrix probe sets were identified whichshowed a significant difference between Control and CR50 or Control andCR70 groups. 4,729 probe sets were identified which exhibited aBenjamini adjusted p value of p<0.05. From the 4,729 probe sets, 208genes were identified which demonstrated rank ordered expression withregard to level of deprivation (Control<CR50<CR70, N=64;Control>CR50>CR70, N=144). These 208 probe sets showing rank orderedexpression are provided in Table 7. Rank ordered expression of the genesindicates that the gene expression in rats at 50% caloric restriction(CR50) was increased relative to the control rats (CR50>CONT) and wherethe gene expression in rats at 70% caloric restriction (CR70) wasincreased relative to the CR50 rats (CR70>CR50). These rats aredesignated “TRUE” in the “upup” column. Alternatively, rank orderedexpression of the genes may indicate that the gene expression in rats at50% caloric restriction (CR50) was decreased relative to the controlrats (CR50<CONT) and where the gene expression in rats at 70% caloricrestriction (CR&)) was decreased relative to the CR50 rats (CR70<CR50).These rats are designated “TRUE” in the “downdown” column. From thelatter set of 208 genes, 5 exemplar genes were selected to include inthe analysis. As with the HF gene selection, there was no systematicbasis for this selection other than the probe set had an identified genename. The 5 genes selected are shown below in Table 8. Table 8 shows theindividual expression (log units) for the CR70 group (group 1), CR50group (group 2), and the control group (group 3) for vascular adhesionmolecule 1 (probe set 1368474) (designated “G7”).

TABLE 8 PROBE SET NAME FUNCTION 1369132 solute carrier 18, member 2neurotransmitter transport 1368474 vascular adhesion cell adhesionmolecule 1 1388116 collagen type 1 alpha collagen 1368558 allograftinflammatory macrophage activation factor 1 1387796 arachidonate 12electron transport lipoxygenase

Discriminant Analysis of Four Nutritional Groups

The data for the 10 genes identified above in Tables 5 and 8 wasanalyzed for each of the 24 animals (8 Control, 5 CR50, 5 CR70, 6 HF)utilizing a Discriminant Analysis, which allows for the classificationof a set of observations into predefined classes. From the expressionlevel data for all 10 genes, Discriminant Analysis producesprobabilities for group membership, which in turn allows for a projectedgroup classification. The results from this analysis are shown in Table9. Based upon the Discriminant Analysis, the expression levels of these10 genes was used to predict the membership of the each animal to aparticular group, i.e., the control group, CR50 group, CR70 group, orthe HF group. Based upon the discriminant analysis, each animal wascorrectly classified into the correct group with 100% accuracy. Theseresults support the hypothesis that prospectively defined sets of genes,given appropriate weighting values can be used to classify individualinfants with regard to at least some important characteristics of theretheir prenatal nutritional experiences. This provides a valuable toolfor determining if prenatal growth was optimal, and as a potential guidefor future treatment of the newborn infant.

Discrimination and Specificity of SSRI Exposure

In order to determine whether placental gene expression profiling can beused to identify other prenatal exposures such as toxicants and drugs, agroup of rats with drug exposure was monitored as described above. TheSSRI group described above were fed a serotonin selective reuptakeinhibitor (SSRI, Fluoxetine) in their drinking water throughoutpregnancy at a dose of approximately 10 mg/kg/day. This dosage wasestimated based upon the average water intake per day per animal,average size of the animals, and the dosage of fluoxetine provided inthe water. As with control, CR50, CR70, and HF groups, placentas fromthe mothers were sampled after 21 days of gestation and gene expressionmonitored utilizing an Affymetrix Rat Genome Chip. Although many fewergenes were affected by this treatment than for either caloricrestriction or high fat diets, expression of 281 probe sets was alteredby exposure to fluoxetine. These probe sets are shown in Table 10. Ofthe 10 genes showing the greatest increase or decrease in expression,relative to the control group, none were among the genes affected by theHF diet (at the p<0.001 level), and none were among the genes thatexhibited dose response effects of caloric restriction. This datasupports the hypothesis that placental gene expression profiling canprovide specific markers of drug exposure.

Development of a Caloric Restriction Score

Utilizing statistical analysis methods, a caloric restriction score canbe generated based upon gene expression data. The caloric restrictionscore may be used to determine dietary conditions during pregnancy.

To generate a caloric restriction score, linear regression formulas arefirst generated for each gene being examined. To generate linearregression formulas, genes which have been identified to bedifferentially expressed based upon dietary restrictions duringgestation are selected. The data samples are collected for genes fromsubjects which experience varying levels of dietary restriction duringpregnancy. The data sample for each gene is assigned an arbitrary valuedepending upon the dietary restrictions during gestation. It will berecognized that the arbitrary value is useful for the purposes ofstatistical analysis to provide a comparative value between datasamples, and the selection of appropriate values will be within thecapabilities of a person of ordinary skill in the art. For example, datasamples from control subjects which are under no dietary restriction maybe assigned a value of 1 (one), data samples from subjects with a 50%dietary restriction (caloric intake reduced by 50%) may be assigned avalue of 2 (two), and data samples with a 70% dietary restriction(caloric intake reduced by 70%) may be assigned a value of 3 (three).Alternatively, values corresponding to the level of dietary restrictionmay be assigned. For example, data samples from control subjects whichare under no dietary restriction may be assigned a value of 100(representing 100% caloric intake, i.e., subjects fed ad libitum), datasamples from subjects with a 50% dietary restriction (caloric intakereduced by 50%) may be assigned a value of 50 (representing 50% caloricintake, relative to subjects fed ad libitum), and data samples with a70% dietary restriction (caloric intake reduced by 70%) may be assigneda value of 30 (representing 30% caloric intake, relative to subjects fedad libitum). The data samples for each gene are analyzed by a linearregression model, and a weighting factor (i.e., slope or beta weight) isgenerated for the gene. Based upon the weighting factor and linearregression model, a linear regression formula is deduced which may beused to determine intercept values for the expression of the gene in agiven sample, by inputting the gene expression data.

A caloric restriction score can be computed as a composite score of thegene expression for each gene being examined. An example of linearregression data and a formula for calculating the caloric restrictionscore can be seen in Table 3 and Table 4, utilizing the genesrepresented by the probe sets listed in Table 8. By way of example, acaloric restriction score can be computed for five genes (G6, G7, G8,G9, and G10) utilizing the following formula:

(Caloric Restriction Score)=(Constant)+(G6 coefficient)×(G6expression)+(G7 coefficient)×(G7 expression)+(G8 coefficient)×(G8expression)+(G9 coefficient)×(G9 expression)+(G10 coefficient)×(G10expression)

The (Constant) variable may be calculated as the intercept value from alinear regression model based on the expression of all genes beingexamined, i.e., G6, G7, G8, G9, and G10. In the exemplary formula above,the “G6 coefficient” represents the weighting factor determined via thelinear regression analysis for gene G6, the “G7 coefficient” representsthe weighting factor determined via the linear regression analysis forgene G7, the “G8 coefficient” represents the weighting factor determinedvia the linear regression analysis for gene G8, the “G9 coefficient”represents the weighting factor determined via the linear regressionanalysis for gene G9, the “G10 coefficient” represents the weightingfactor determined via the linear regression analysis for gene G10. Itwill be apparent to a person of ordinary skill in the art that more orfewer genes may be utilized to calculate the caloric restriction scoreby adding or removing terms to the above equation.

The results from the Control group, the CR50 group (50% dietaryrestriction), and the CR70 group (70% dietary restriction) were used toconstruct a Caloric Restriction Score (CRS). Statistical analysis of thedata was run utilizing Systat™ software (available from Systat Software,Inc., Point Richmand, Calif.). The caloric restriction formula was firstproduced for each of the 5 genes that were significantly related tocaloric restriction by running a linear regression model, wherein theControl group was assigned a value of 1, the CR50 group was assigned avalue of 2, and the CR70 group was assigned a value of 3. From theseformulas, a weighting factor for each gene was derived and interceptscalculated for the gene expression of each gene for each animal. Thesevalues were then used to produce a CRS for each animal. FIG. 9 shows themeans and standard errors for these predicted CRSs for each group. Aswould be expected, the CRS increases above Control levels withincreasing levels of caloric restriction. In addition, this analysisindicates that the profile of gene expression for the high fat group(HF) and the SSRI exposed group (SS) do not fit a pattern consistentwith overall caloric restriction.

Alternatively, the linear regression model may be calculated wherein theControl group is assigned a value of 100, the CR50 group is assigned avalue of 50, and the CR70 group is assigned a value of 30. The remainingsteps are performed as described above. The complete data resulting fromthis analysis can be found in Tables 3 and 4. FIG. 10 shows the meansand standard errors for these predicted CRSs for each group. The caloricrestriction score resulting from this analysis indicates the predictedpercent of normal nutrition. Based upon this analysis, the body weightsof rat fetuses were measured at day 21, i.e., the day before expecteddelivery, and the body weights compared to the caloric restriction scoregenerated for each fetus. FIG. 11 shows the relationship between bodyweight and the caloric restriction score representing the predictedpercent of normal nutrition. This data demonstrates that the caloricrestriction score can be used to track group mean differences, but alsocan provide a good marker for individual level of caloric restrictionand fetal growth.

Example 3 Effect of Caloric Restriction During Pregnancy on PlacentalGene Expression in Rats

Gene expression from placentas of 6 control and 5 food restricted (70%)pregnancies were measured in rats. Placentas from 6 pups from eachlitter were pooled. RNA was extracted and over 30,000 genes andexpressed sequences were analyzed using Affymetrix chips. Of that total,6143 (˜20%) showed no overlap in expression between control and IUGRplacentas. Of the 6143, 2819 (˜46%) were down-regulated, and 3324 (˜54%)were up-regulated.

Within the group of down-regulated genes there are five fibroblastgrowth factor genes and 16 solute carrier genes including thefacilitated glucose transporter (Slc2a5) that are significantly alteredthe caloric restriction. In addition, several insulin-related genes weredown regulated including, insulin itself (Ins 2), insulin degradingenzyme, insulin receptor-related receptor, insulin-like growth factor I,insulin-like growth factor binding protein 6, and insulin-like growthfactor binding protein 5. Within the up-regulated gene group there are 6genes associated with calcium channels, corticotrophin receptor hormone(CRH) binding protein and CRH receptor, and 6 fibroblast growth factors.There were also 11 solute carrier genes that were up-regulated including2 amino acid transporters (1-proline and a cationic AA transporter). Theinsulin-like protein 6 and insulin-like growth factor 2 were also amongthis group.

Data analysis is being conducted to characterize the patterns of changeand functional clusters of genes that are altered by prenatalmalnutrition. Assays based upon expression of the identified genes willafford new strategies for determining if individual fetuses have beensubjected to deviations from normal patterns of nutrient delivery. Geneexpression in rats also provides candidate genes to be assayed in humanplacental samples.

Placental Gene Expression in Growth Restriction: Comparison of Rat andHuman Microarray Studies.

In the 70% restriction model in rats discussed above, several hundredgenes were found that show no overlap between control and under-growngroups. To determine if at least some of these changes might also berelated to under-growth of the human fetus, the results were comparedwith recently published work by McMinn and colleagues. McMinn et al.,supra. McMinn examined mRNA expression in 14 IUGR placentas withmaternal vascular under-perfusion compared to 15 non-IUGR placentasusing Affymetrix microarrays. As was the case in the rat study above,McMinn found numerous differences in expression in IUGR placentas. Id.For example, increased expression of PHLDA2 and decreased expression ofMEST, MEG3, GATM, GNAS and PLAGL1 in IUGR placentas was found. Id. Inaddition to imprinted genes, differences were detected in endocrinesignaling (LEP, CRH, HPGD, INHBA), tissue growth (IGF1), immunemodulation (INDO, PSG-family genes), oxidative metabolism (GLRX),vascular function (AGTR1, DSCR1) and metabolite transport (SLC-familysolute carriers). Id.

Comparison of the data from McMinn and the present rat studies resultedin several lists of genes, shown in Table 2. McMinn et al., supra. Table2 contains genes that were observed to have increased expression in boththe caloric restriction rat model and in McMinn's IUGR human analyses.Table 2 also provides a list of genes with reduced expression in bothdata sets. Lastly, Table 2 provides lists of genes with reducedexpression in one data set, and increased expression in the other dataset. This comparative data supports the hypothesis that there will bedistinct patterns of placental gene expression associated with fetalover-growth. The specificity of these patterns are tested by enrichinggroups of infants with those exhibiting catch-down growth during theearly postnatal period and by convergent results obtained fromexperimental manipulation of weight gain in an animal model.

Example 4 Placental Gene Expression Results from Prenatal AlcoholExposure Study

Microarray placental gene expression results were obtained from a totalof 18 pregnancies; 9 animals with no exposure to alcohol, 5 given 5%alcohol in their drinking water throughout pregnancy, and 4 given 10%alcohol in their drinking water throughout pregnancy. The Affymetrixchip for the rat genome quantifies expression of 31,101 probe sets, andidentifies sequences of mRNA known to be expressed in the rat. Because alarge number of comparisons between exposed and unexposed animals arepossible, a statistical strategy was devised to reduce the likelihood offinding false positives. For the first phase of analysis three criteriawere combined to reduce the problem of false discovery. First, t-testswere performed for all probe sets, testing for differences betweencontrol and 5% samples. This is shown in Tables 11 and 12, in thecolumns marked “T-val contr.vs.5.” Second, t-tests were performed forall probes sets, testing for differences between 5% and 10% samples.This is shown in Tables 11 and 12, in the columns marked “T-val 5 vs.10.” To be included in the list of candidate genes, it was required thatthe probability of a significant difference between groups (identifiedutilizing the p-value) was less than 0.05 for both tests. The combinedprobability of false detection was thus 0.05×0.05, or 0.0025. Inaddition, the genes were included only if group differences were orderedin 2 of the four possible ways; 0<5%<10% or 0>5%>10%. This is shown inTables 11 and 12 in the columns marked “Contr<5,” “5<10,” “c<5<10,”“Contr>5,” “5>10,” and “c>5>10.” Thus, for each of the two possiblepatterns of group differences, the overall expected rate of falseidentification was 0.05×0.05×0.25(one quarter of the possiblepatterns)×31,101=19 genes.

Using the above criteria 57 probe sets were identified with reducedexpression in the alcohol exposed animals (that is, the 0>5%>10% patternof group differences), or approximately 3 times more than would beexpected by chance alone. The probe sets with reduced expression in thealcohol exposed animals selected under the criteria described above areshown in Table 11. In contrast, only 8 probe sets were identified asbeing up-regulated by alcohol, thus giving less confidence that thistype of change was due to chance alone. The probe sets with increasedexpression in the alcohol exposed animals selected under the criteriadescribed above are shown in Table 12.

Following this screening procedure it was next determined which of the65 potential alcohol responsive genes were found in prior data sets thathad tested for effects of caloric restriction, high fat diets, and SSRI(such as fluoxetine) exposure during pregnancy. The prior data for theeffects of caloric restriction, high fat diets, and SSRI exposure duringpregnancy are reflected in Tables 11 and 12 in the columns marked “sigSSRI,” “Sig HF,” “Sig MMMCR,” “sig up,” and “sig down.” After excludingall overlapping genes, 35 placental genes remained that weredown-regulated by exposure to alcohol and 7 placental genes remainedthat were up-regulated by exposure to alcohol. The 35 genes remainingthat were down regulated by alcohol are shown by the shaded rows inTable 11. The 7 remaining genes that were up regulated by alcohol areshown by the shaded rows in Table 12.

From this list of 42 candidate genes 6 probes were chosen for furtheranalysis that were identified as genes that showed the most pronouncedgroup differences. Expressed sequences which have not been characterizedas known genes were not included. The 5 down-regulated genes were:peroxisomal biogenesis factor 6 (Pex6), cell division cycle associated 7(Cdca7), TP53 regulating kinase (Trp53rk), pleckstrin (Plek), andinositol polyphosphate-1-phosphatase (Inpp1). The one up-regulated geneincluded was Zinc finger protein 365 (Zfp365).

FIG. 12 shows the mean (±SE) expression values for each of these 6genes. As can be seen in this figure, there is a clear dose-responsechange in expression associated with alcohol exposure during pregnancy.A multivariate regression analysis was performed to determine how wellexpression levels of these 6 genes predicated alcohol exposure. As canbe seen in Table 13, together these genes were highly predicted of levelof alcohol exposure, accounting for 96.4% of the variance in exposure.

TABLE 13 Results from multivariate analysis of variance using expressionof 6 candidate genes to predict level of alcohol exposure. DEP VAR:ALCAMT N: 18 R = 0.982 R² = 0.964 P < .001 VARIABLE COEFFICIENT STDERROR STD COEF TOLERANCE T P(2 TAIL) INTERCEPT 19.668 11.979 0.000 —1.642 0.129 PEX6 −1.168 1.377 −0.130 0.138 −0.849 0.414 CDCA7 −2.0380.928 −0.291 0.184 −2.197 0.050 TP53 −0.775 2.014 −0.063 0.121 −0.3850.708 PLEK −0.290 1.187 −0.037 0.137 −0.244 0.812 INPP1 −2.925 1.034−0.268 0.361 −2.827 0.016 ZFP365 5.229 1.864 0.304 0.274 2.805 0.017

Next, to determine how accurately expression levels of these genes couldestimate level of alcohol exposure, the coefficients from the regressionmodel were used to calculate estimated values. FIG. 13 shows the meanestimates for alcohol exposure for each group compared to the actualexposure. As can be seen in this figure, expression levels of thesegenes can be used to produce very accurate estimates of exposure level.

Finally, discriminate analysis was performed which used the geneexpression values to predict exposure group membership. As can be seenin Table 14, by combining expression values from these six genes, whichplacentas were in which exposure group could be predicted with 100%accuracy.

TABLE 14 Actual Treatment Group Control 5% 10% Predicted Control 9 0 0Group  5% 0 5 0 10% 0 0 4

Together, these results clearly indicate that quantifying profiles ofgene expression in the placenta affords a novel strategy for assessmentof level and specificity of alcohol exposure during fetal development.

Various references are cited herein, which are hereby incorporated byreference in their entireties.

TABLE 1 Change in Change in Change in Probe Set expression Probe Setexpression Probe Set expression 1371198_at down 1392413_at down1377863_at up 1383551_at down 1392416_at down 1391156_at up 1388544_atdown 1392526_at down 1379272_at up 1369124_at down 1392571_at down1376008_at up 1387493_at down 1392584_at down 1389247_at up 1390662_atdown 1392600_a_at down 1371958_at up 1387909_at down 1392607_at down1374175_at up 1383740_at down 1392608_at down 1390473_at up 1385123_atdown 1392609_at down 1390250_x_at up 1380504_at down 1392637_at down1390816_at up 1370856_at down 1392641_at down 1375301_at up 1388128_atdown 1392675_at down 1393692_at up 1369341_a_at down 1392680_at down1392436_at up 1387276_at down 1392683_at down 1393274_at up 1369526_atdown 1392686_at down 1382504_at up 1369734_at down 1392762_at down1376279_at up 1376022_at down 1392846_at down 1375332_at up 1368933_atdown 1392962_at down 1390044_at up 1368370_at down 1393041_at down1378196_at up 1380643_at down 1393077_at down 1383685_at up 1376268_atdown 1393154_at down 1374828_at up 1374178_at down 1393187_at down1393642_at up 1389967_at down 1393291_at down 1380873_at up 1368021_atdown 1393298_at down 1372603_at up 1391657_at down 1393432_a_at down1382812_at up 1368558_s_at down 1393434_at down 1381536_at up 1377700_atdown 1393446_at down 1388519_at up 1393596_at down 1393479_at down1386422_at up 1378955_at down 1393492_at down 1389653_at up 1388007_x_atdown 1393512_at down 1385435_at up 1368465_at down 1393514_at down1377079_a_at up 1392135_at down 1393515_at down 1373741_at up 1372615_atdown 1393529_at down 1385298_at up 1393000_at down 1393530_at down1391231_at up 1387289_at down 1393547_at down 1391392_at up 1370846_atdown 1393577_at down 1393300_at up 1387100_at down 1393580_at down1375326_at up 1368621_at down 1393597_at down 1393307_at up 1387796_atdown 1393607_at down 1374332_at up 1367988_at down 1393615_at down1395401_at up 1369026_at down 1393653_at down 1392246_at up 1369873_atdown 1393734_at down 1398422_at up 1393958_at down 1393820_at down1391340_at up 1397415_at down 1393927_at down 1397312_at up 1370350_x_atdown 1394079_at down 1397747_at up 1397224_at down 1394107_at down1378704_at up 1369342_at down 1394129_at down 1373631_at up 1368769_atdown 1394259_at down 1375156_at up 1370465_at down 1394283_at down1392092_at up 1398265_at down 1394284_at down 1397314_at up 1368561_atdown 1394434_at down 1379311_at up 1387184_at down 1394447_at down1394037_at up 1390429_at down 1394455_at down 1376855_at up 1369248_a_atdown 1394504_at down 1374962_at up 1369084_a_at down 1394528_at down1396087_at up 1373733_at down 1394549_at down 1373593_at up 1368482_atdown 1394551_at down 1383500_at up 1388144_at down 1394577_at down1371445_at up 1371440_at down 1394578_at down 1375560_at up 1375284_atdown 1394584_at down 1377083_at up 1369426_at down 1394630_at down1398372_at up 1378427_at down 1394694_at down 1374114_at up 1388075_atdown 1394699_at down 1394523_at up 1387938_at down 1394717_at down1377448_at up 1370849_at down 1394756_at down 1389171_at up 1389821_atdown 1394801_at down 1376603_at up 1387540_at down 1394809_at down1388665_at up 1377817_at down 1394820_at down 1376192_at up 1371199_atdown 1394861_at down 1386194_at up 1368523_at down 1394890_at down1376239_at up 1368642_at down 1394891_at down 1379809_at up 1370657_atdown 1394919_at down 1394519_at up 1397177_at down 1394933_at down1384318_at up 1369647_at down 1394971_at down 1377252_at up 1377640_atdown 1395010_at down 1377268_at up 1378073_at down 1395028_at down1375351_at up 1370133_at down 1395056_at down 1371534_at up 1377518_atdown 1395057_at down 1379254_at up 1389824_at down 1395096_at down1396059_at up 1368156_at down 1395151_at down 1375076_at up 1368955_atdown 1395194_at down 1391865_at up 1376345_at down 1395203_at down1384884_at up 1368823_at down 1395207_at down 1384670_at up 1384532_atdown 1395218_at down 1391840_at up 1368131_at down 1395260_at down1373728_at up 1387991_at down 1395359_at down 1381407_at up 1367785_atdown 1395368_at down 1385001_at up 1368905_at down 1395373_at down1373071_at up 1370363_at down 1395383_at down 1375208_at up 1368913_atdown 1395389_at down 1381991_at up 1369186_at down 1395390_at down1385885_at up 1387690_at down 1395432_at down 1395913_at up 1368637_atdown 1395433_at down 1373023_at up 1387005_at down 1395438_at down1393203_at up 1369865_at down 1395499_at down 1376500_at up 1368555_atdown 1395575_at down 1386614_at up 1368975_at down 1395635_at down1395647_at up 1369483_at down 1395656_at down 1371452_at up 1370891_atdown 1395726_at down 1377945_at up 1367679_at down 1395747_at down1395190_at up 1395116_at down 1395762_at down 1377837_at up 1388013_atdown 1395820_at down 1397884_at up 1388053_at down 1395834_at down1390418_at up 1384085_at down 1395902_at down 1375876_at up 1382113_atdown 1395912_at down 1379228_at up 1378832_at down 1396057_at down1392671_at up 1370391_at down 1396071_at down 1397683_at up 1393680_atdown 1396119_at down 1397882_at up 1375977_at down 1396157_at down1383911_at up 1383121_at down 1396162_at down 1383779_at up 1387709_atdown 1396281_at down 1389777_at up 1369983_at down 1396343_at down1382187_at up 1387969_at down 1396377_at down 1374484_at up 1379365_atdown 1396378_at down 1391626_at up 1369633_at down 1396520_at down1376866_at up 1387956_s_at down 1396577_at down 1389888_at up 1397076_atdown 1396602_at down 1380265_at up 1376800_at down 1396607_at down1374634_at up 1394833_at down 1396613_at down 1380152_at up 1387032_atdown 1396619_at down 1390481_a_at up 1369112_at down 1396669_at down1398374_at up 1368734_at down 1396670_at down 1394216_at up 1388054_a_atdown 1396725_at down 1383902_at up 1388142_at down 1396796_at down1379759_at up 1388265_x_at down 1396807_at down 1383891_a_at up1371672_at down 1396815_at down 1394509_at up 1369951_at down 1396837_atdown 1383128_at up 1368658_at down 1396854_at down 1379981_at up1376711_at down 1396863_at down 1376501_at up 1389944_at down 1396947_atdown 1377848_at up 1378431_at down 1396979_at down 1393773_at up1369800_at down 1396980_at down 1394960_at up 1382194_at down 1396997_atdown 1381755_x_at up 1374779_at down 1397034_at down 1372712_at up1369724_at down 1397048_at down 1391501_at up 1384063_at down 1397081_atdown 1391749_a_at up 1376099_at down 1397109_at down 1385650_at up1369529_at down 1397122_at down 1374980_at up 1387893_at down 1397125_atdown 1385154_at up 1368695_at down 1397135_at down 1378312_at up1368742_at down 1397158_at down 1378788_at up 1387446_at down 1397195_atdown 1394458_at up 1376051_at down 1397346_at down 1373177_x_at up1393008_at down 1397369_at down 1380032_at up 1387496_a_at down1397374_at down 1389472_at up 1387897_at down 1397376_at down 1389140_atup 1383075_at down 1397404_at down 1398177_at up 1368083_at down1397428_at down 1389641_at up 1387296_at down 1397431_at down 1391609_atup 1371274_at down 1397560_at down 1395638_at up 1369113_at down1397585_at down 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1377534_at up1398661_at up 1392212_at down 1374590_at up 1398671_at up 1392236_atdown 1384912_at up 1398715_at up 1392245_at down 1385197_at up1392250_at down 1386152_at up 1392252_at down 1392829_at up 1392274_atdown 1396395_at up 1392293_at down 1398216_at up

TABLE 2 Up regulated in IUGR and CR proviral integration site 1homocysteine-inducible, endoplasmic reticulum stress-inducible,ubiquitin- like domain member 1 Protein C receptor, endothelial(predicted) Solute carrier family 2 (facilitated glucose transporter),member 2 glycoprotein hormones, alpha subunit similar to hypotheticalprotein FLJ13511 (predicted) phospholipase C-like 2 (predicted) similarto Hypothetical WD-repeat protein CGI-48 (predicted) peroxiredoxin 6Sorting nexin 10 (predicted) leptin Similar to IER7 Small fragmentnuclease (predicted) Tissue factor pathway inhibitor Similar to IER6syndecan 1 Jun D proto-oncogene huntingtin interacting protein 2(predicted) Ferredoxin 1 solute carrier family 11 (proton-coupleddivalent metal ion transporters), member 2 neuron specific gene familymember 1 Hydroxysteroid dehydrogenase-1, delta<5>-3-beta (predicted)Down regulated in both iugr and cr Catalase colony stimulating factor 1(macrophage) Zinc finger protein 262 (predicted) immunoglobulin (CD79A)binding protein 1 Hepatocyte growth factor bone morphogenetic protein 5(predicted) adaptor-related protein complex 3, mu 2 subunit Similar tohypothetical protein FLJ22344 (predicted) Glycine amidinotransferase(L-arginine: glycine amidinotransferase) similar to map kinaseinteracting kinase SMC6 structural maintenance of chromosomes 6-like 1(yeast) (predicted) aquarius (predicted) sprouty homolog 2 (Drosophila)(predicted) cytoplasmic FMR1 interacting protein 1 (predicted) similarto TBC1 domain family member 4 folate receptor 2 (fetal) (predicted)mitogen-activated protein kinase kinase kinase kinase 4 (predicted)Adducin 3 (gamma) FERM domain containing 4B dystonin (predicted)O-linked N-acetylglucosamine (GlcNAc) transferase (UDP-N-acetylglucosamine: polypeptide-N-acetylglucosaminyl transferase)platelet derived growth factor receptor, beta polypeptidelysosomal-associated protein transmembrane 4B (predicted) myosin X(predicted) laminin, alpha 2 (predicted) low density lipoproteinreceptor-related protein 6 (predicted) ubiquitin conjugation factor E4 Atransforming growth factor beta 1 induced transcript 1 RT1 class I, CE16RT1 class Ia, locus A2 procollagen, type XV (predicted) protocadheringamma subfamily C, 3 CD4 antigen stabilin 1 (predicted) guanylatecyclase 1, soluble, beta 3 Ras homolog gene family, member E procollagenC-proteinase enhancer protein peripheral myelin protein 22 fibromodulinwingless-related MMTV integration site 2 CD44 antigen intercellularadhesion molecule 2 myeloid cell nuclear differentiation antigen(predicted) complement component 1, r subcomponent (predicted)dihydropyrimidinase-like 3 RT1 class I, CE15 RT1 class Ib, locus Aw2RT1-149 protein amine oxidase, copper containing 3 procollagen, type VI,alpha 3 (predicted) Cytochrome b-245, beta polypeptide Neuropilin 1caspase 1 Down syndrome critical region homolog 1 (human) Similar toE430002G05Rik protein (predicted) Collagen, type V, alpha 2 Nuclearreceptor subfamily 3, group C, member 1 similar to hypothetical proteinFLJ10652 (predicted) guanylate cyclase 1, soluble, alpha 3 potassiumvoltage-gated channel, delayed-rectifier, subfamily S, member 3procollagen, type I, alpha 3 insulin-like growth factor 1 allograftinflammatory factor 1 allograft inflammatory factor 2 procollagen, typeI, alpha 2 plasma glutamate carboxypeptidase Down in IUGR and Up in CRCUG triplet repeat, RNA-binding protein 2 aldehyde dehydrogenase family3, subfamily A2 core-binding factor, runt domain, alpha subunit 2;translocated to, 1; cyclin D-related (predicted) collagen, type V, alpha3 Nuclear receptor subfamily 2, group F, member 2 ATPase, Ca++transporting, cardiac muscle, slow twitch 2 similar to dJ202D23.2 (novelprotein similar to C21ORF5 (KIAA0933)) (predicted) Transducin-likeenhancer of split 4, E(spl) homolog (Drosophila) Potassium channel,subfamily K, member 3 apurinic/apyrimidinic endonuclease 1 gap junctionmembrane channel protein alpha 1 ATPase, Ca++ transporting, plasmamembrane 4 Transducin-like enhancer of split 4, E(spl) homolog(Drosophila) Solute carrier family 5 (inositol transporters), member 3Klotho tripartite motif protein 27 (predicted) myosin Ib chromosomecondensation 1-like thymus cell antigen 1, theta CTD (carboxy-terminaldomain, RNA polymerase II, polypeptide A) small phosphatase-like(predicted) cAMP responsive element binding protein 1 Ectonucleotidepyrophosphatase/phosphodiesterase 2 LRRC36 homolog (human) Growth arrestspecific 6 CDC16 cell division cycle 16 homolog (S. cerevisiae)(predicted) matrix metallopeptidase 2 UP in IUGR and Down in CR Similarto RIKEN cDNA 1500006O09 (predicted) growth differentiation factor 15Basic leucine zipper and W2 domains 4 colony stimulating factor 2receptor, beta 1, low-affinity (granulocyte- macrophage) eukaryotictranslation termination factor 1 (predicted) similar to RIKEN cDNA1110012L19 Similar to RIKEN cDNA 3930401K13 (predicted)ubiquitin-conjugating enzyme E2 variant 2 Tankyrase, TRF1-interactingankyrin-related ADP-ribose polymerase 2 (predicted) RAS guanyl releasingprotein 1 ornithine decarboxylase antizyme inhibitor Thymine-DNAglycosylase microfibrillar-associated protein 3-like (predicted) actinrelated protein ⅔ complex, subunit 5-like (predicted) polymerase (RNA)II (DNA directed) polypeptide H (predicted) ectonucleoside triphosphatediphosphohydrolase 1 microtubule-associated protein 7 (predicted)Tankyrase, TRF1-interacting ankyrin-related ADP-ribose polymerase 2(predicted) Similar to methyl-CpG binding protein MBD2 cytochrome P450,family 19, subfamily a, polypeptide 1 hexosaminidase B (predicted)Similar to testis specific protein, Ddc8 Serine/threonine kinase 3inhibin beta-A microfibrillar associated protein 5 (predicted) GULP,engulfment adaptor PTB domain containing 1 (predicted) solute carrierfamily 11 (proton-coupled divalent metal ion transporters), member 3calpain 6 Transferrin receptor

TABLE 3 Body Log Predicted wt @ placenta base 2 percent 21days wt atexpression placenta/ of normal SUB SUBNUM NUMPUPS gest 21 days GROUPGROUP$ NUTR for G6 G7 G8 G9 G10 body wt nutrition 431 1 1 cont 100 9.446.39 8.64 5.26 8.03 93.23607 434 2 1 cont 100 9.49 6.29 8.35 5.71 7.5292.90031 6063 3 14 5.35 0.59 1 cont 100 9.08 5.64 8.32 5.66 7.80.110280374 81.99082 6078 4 12 4.74 0.61 1 cont 100 9.4 6.31 9.52 5.558.23 0.128691983 100.7257 6081 5 16 4.27 0.602 1 cont 100 9.32 6.11 8.755.28 7.47 0.140983607 80.80017 6082 6 15 5.78 0.568 1 cont 100 9.56 6.359.27 5.44 8.3 0.098269896 97.44234 6089 7 16 6.12 0.578 1 coot 100 9.266.57 9.2 5.93 8.38 0.094444444 120.72533 7000 8 15 4.4 0.585 1 cont 1009.26 6.06 9.24 5.32 9.03 0.132954545 99.36833 430 9 2 cr50 50 9.36 5.798.02 5.1 7.29 63.71409 461 10 2 cr50 50 8.35 5.14 8.18 4.49 7.0945.71904 480 11 2 cr50 50 8.98 5.69 7.73 4.97 7.19 62.94884 520 12 2cr50 50 9.09 5.39 6.85 4.77 7.52 50.54269 522 13 2 cr50 50 8.78 4.9 7.215.06 7.45 46.49589 6052 14 15 2.56 0.362 3 cr70 30 8.54 4.89 7.83 4.746.58 0.14140625 34.02256 6070 15 16 2.71 0.322 3 cr70 30 8.22 4.75 7.114.24 6.63 0.118819188 24.39289 6073 16 15 1.69 0.349 3 cr70 30 8.36 4.657.4 4.47 6.72 0.206508876 25.13745 6081 17 11 2.89 0.4 3 cr70 30 8.674.68 7.19 4.93 7.22 0.138408304 36.16791 6088 18 14 3.16 0.378 3 cr70 308.86 5.12 8.34 4.82 7.1 0.119620253 43.72432 447 19 4 high fat 8.08 5.368.44 5.31 8.11 86.58862 448 20 4 high fat 8.57 5.35 9.12 5.69 8.3989.8461 475 21 4 high fat 8.22 5.79 7.61 5.46 8.03 99.03123 476 22 4high fat 8.46 5.54 8.4 5.33 7.74 81.80713 477 23 4 high fat 8.08 4.597.73 4.47 8.35 46.9611 490 24 4 high fat 8.77 6.9 7.47 6.17 7.19129.35374 423 25 5 ssri 8.97 5.83 8.34 5.07 7.19 70.1036 424 26 5 ssri9.76 6.83 8.25 5.61 7.79 105.7582 462 27 5 ssri 8.56 5.81 7.56 6.11 8.37111.63444 463 28 5 ssri 8.71 5.78 7.7 5.44 8.23 92.27523 486 29 5 ssri8.41 6.62 7.57 5.3 6.76 103.37632 493 30 5 ssri 9.1 6.05 7.69 5.39 8.0390.5559

TABLE 4 Results from regression model (output from Systat). DEP VAR:NUTR N: 18 MULTIPLE R: 0.942 SQUARED MULTIPLE R: 0.888 ADJUSTED SQUAREDMULTIPLE R: .841 STANDARD ERROR OF ESTIMATE: 12.618 VARIABLE COEFFICIENTSTD ERROR STD COEF TOLERANCE T P(2 TAIL) CONSTANT −154.181 112.434 0.000. −1.371 0.195 G6 −17.098 19.339 −0.232 0.137 −0.884 0.394 G7 30.79214.584 0.650 0.099 2.111 0.056 G8 0.860 7.287 0.022 0.260 0.118 0.908 G921.483 13.291 0.316 0.245 1.616 0.132 G10 11.411 8.265 0.238 0.315 1.3810.193 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIOP REGRESSION 15089.559  5 3017.912 18.956 0.000 RESIDUAL 1910.441 12159.203 percent normal nutrition = −154.181 + (−17.098 * G6) + (30.792 *G7) + (.860 * G8) + (21.483 * G9) + (11.411 * G10)

TABLE 6 ProbeSet HF HF HF HF HF HF Cont 1368220_at 11.00438 10.9460510.97849 10.82925 10.77598 10.84353 9.758575 1374716_at 8.5049498.337197 8.454606 8.369065 8.498878 8.321859 7.382849 1389323_at11.19787 11.19813 11.25418 10.92503 10.84815 11.09756 9.7599441372137_at 9.386279 9.075376 9.245911 9.20572 9.138822 9.133685 8.3404761372829_at 10.74478 10.70918 10.75531 10.48642 10.55559 10.547469.530819 1382415_at 9.290794 9.198184 9.485319 9.122929 9.0709759.284197 8.184726 1398572_at 10.39127 10.49282 10.33323 10.08627 10.270510.15836 9.456452 1372269_at 10.01691 10.23635 10.16678 9.7850239.890261 10.07748 9.077942 1373711_at 7.725819 7.36752 7.445315 7.5383017.501101 7.496567 6.459201 1379623_at 8.773002 8.615665 8.3938218.511766 8.50896 8.510308 7.49858 1387663_at 9.887677 9.71076 9.6433369.547209 9.627646 9.905763 8.806636 1371745_at 10.3637 10.57099 10.4992310.27754 10.19192 10.20092 9.326018 1372977_at 9.093507 8.8519058.944857 8.923531 8.608058 8.767383 7.736954 1373490_at 9.3223299.468861 9.402854 9.064308 9.233554 9.229498 8.489771 1372209_at10.91862 10.90722 10.74615 10.68275 10.70574 10.82427 10.163731374790_at 8.410971 8.406079 8.159171 8.185976 8.120542 8.3488037.194501 1373632_at 9.313249 9.591816 9.705995 9.044372 9.5739169.369567 8.038482 1377025_at 8.935143 9.215185 8.939571 8.7045029.110838 8.819142 7.718635 1373660_at 8.476786 8.543437 8.3184418.449807 8.369802 8.328536 7.856901 1388171_at 10.46938 10.0645110.12315 10.00891 10.1982 10.23223 9.094078 1375345_at 10.67223 10.3842810.26475 10.56421 10.10392 10.48604 9.266286 1368164_at 7.5158567.450585 7.259456 7.111779 7.292723 7.24609 5.862738 1367929_at 12.4088912.08841 12.32236 12.47241 12.43106 12.48097 11.21979 1367945_at10.58849 10.4998 10.55867 10.4129 10.27551 10.28025 9.601717 1389970_at11.06215 10.34947 10.71797 10.51968 10.99669 10.86433 9.3982791371484_at 9.404498 9.10155 9.194271 9.135844 9.475554 9.397057 8.501461371435_at 12.24045 12.02909 12.13144 12.04379 11.99163 12.1500810.95189 1398770_at 12.01959 12.10871 11.86145 11.84417 11.9131111.98752 10.97417 1371421_at 9.908343 9.688636 9.710867 9.7520259.729484 9.911593 9.06891 1386930_at 10.33022 10.22295 9.972137 10.1707510.26647 9.970412 9.107647 1369588_a_at 11.80843 11.65836 11.6692311.5056 11.77628 11.65619 10.67902 1370321_at 9.636169 9.502361 9.3312739.340487 9.392303 9.397918 8.611631 1382825_at 5.313913 5.7678775.476568 5.596724 5.597936 5.320471 6.251075 1397956_at 4.5517544.662863 5.069054 4.781731 4.740965 4.520352 6.007783 1373982_at7.754149 7.974967 7.922373 7.654488 7.899826 7.620515 6.8853411372436_at 9.427578 9.591035 9.237899 9.347602 9.017403 9.3651848.594843 1389009_at 8.404825 8.449807 8.314396 8.106933 8.1612948.371829 7.761211 1388328_at 10.71814 10.32473 10.382 10.36786 10.1784910.57385 9.56632 1389053_at 9.34087 9.22469 8.879764 8.591748 8.7504918.874844 7.657208 1373184_at 9.090719 8.945809 8.94398 9.218229 9.1242629.104634 8.218808 1389409_at 10.44495 9.58989 9.712718 10.05422 9.7135929.709694 8.351042 1374291_at 7.171646 7.282665 7.383197 7.1070017.205973 6.897464 6.352909 1392517_at 8.955887 8.481499 8.5263068.346758 8.292787 8.334693 7.579317 1370931_at 7.774107 7.7371868.387272 7.980927 8.107859 8.131368 6.964884 1367454_at 11.3518110.96007 11.30247 10.84985 11.04809 11.0709 10.13024 1375329_at 3.4120133.422034 3.392105 3.509135 3.419963 3.579827 3.189142 1375788_at7.343741 7.247983 7.105453 6.678797 7.549122 7.605156 5.6720481367492_at 10.92063 10.69177 10.70298 10.80301 10.85659 10.9212 10.241241373346_at 11.36842 11.36714 11.31991 11.22142 11.35562 11.1135210.54271 1392613_at 5.481221 5.455458 5.248688 5.717384 5.61351 5.3707426.588736 1373868_at 8.665543 8.52902 8.657764 8.287104 8.183376 8.1430347.262546 1388974_at 11.2481 11.39397 10.92157 11.00218 10.7927 11.0929810.16239 1373155_at 8.923241 8.496463 8.39192 8.292827 8.333815 8.4793487.61178 1375423_at 11.23431 10.86617 10.63329 10.62934 10.99127 10.726469.390361 1377983_at 5.938665 5.831154 5.97904 5.707722 5.958846 5.9294675.086642 1374703_at 5.596724 5.999135 5.649075 5.739903 5.7740455.916106 6.929027 1382288_at 8.30569 8.032848 8.033499 8.053241 8.192878.373211 7.415974 1374411_at 8.758145 8.850084 8.902061 8.7981158.748045 8.861299 7.78839 1377748_at 6.027023 6.001341 5.954138 5.8248645.693348 5.679235 4.874882 1377257_at 6.476609 6.330833 6.4491096.550034 6.257298 6.576049 5.625702 1396280_at 7.282989 7.2040927.030595 6.855897 7.193504 6.984796 6.456774 1395832_at 4.7224 4.6923624.768027 4.507789 4.721272 4.78133 4.259237 1379759_at 9.030967 9.00148.848308 8.930095 9.041847 9.064055 8.353512 1387002_at 10.6891610.80265 10.8981 10.36402 10.67421 10.80987 9.690964 1373824_at 11.3253410.97234 11.27261 11.10521 10.69277 11.0942 10.11758 1392258_at 5.7661085.97203 6.222736 5.786221 6.184369 5.8555 5.008726 1392514_at 8.581758.427594 8.617246 8.023539 7.859771 8.294312 7.150292 1390789_at9.424225 9.321047 9.365505 9.471624 9.448804 9.518779 8.7179671387258_a_at 10.92697 10.57541 10.69772 10.70767 10.38302 10.637799.760903 1398107_at 4.337737 4.310229 4.222336 4.304347 4.35013 4.4482683.957803 1398919_at 11.01715 11.24309 11.05123 10.79939 10.8343610.96189 9.989695 1369975_at 10.12799 9.711004 10.07836 9.8650839.787584 9.856238 9.243368 1388798_at 10.52856 10.18319 10.4278510.31944 10.9574 10.33247 9.063936 1373475_at 9.346588 9.791472 9.5526879.289251 9.274326 9.508961 8.316184 1372653_at 10.25368 10.6595310.21312 10.16066 9.608513 9.755047 8.476985 1376144_at 8.857995 8.463228.659594 8.425791 8.828238 8.793244 7.739981 1375416_at 9.8948359.457933 9.5208 9.613246 9.94061 9.521029 8.696179 1371480_at 10.2827410.31081 10.22345 9.669149 10.28217 9.914357 9.121711 1368266_at6.763295 6.734196 7.146474 6.800329 6.929252 7.29395 5.900055 1371783_at10.87707 10.74704 10.87561 10.6618 10.45152 10.78217 9.677347 1387151_at8.951893 9.263478 8.921948 8.555851 8.498266 8.821349 7.9558591386818_at 6.699419 6.44565 6.04898 5.982313 6.401855 6.625793 5.3726141374502_at 9.427487 9.325881 9.220198 9.355511 9.674848 9.35446 8.1888891388217_a_at 11.26729 10.92615 11.06716 11.24955 11.32316 11.2676910.21776 1376576_at 9.620916 9.512235 9.76146 9.354869 9.774289 9.8157229.046168 1370000_at 11.33644 11.27049 10.91856 11.14028 11.7491310.78381 9.470313 1372141_at 10.24416 10.16173 9.862221 9.8519549.969874 10.19664 9.266925 1370393_at 8.989789 9.140623 8.60826 8.1259428.175069 8.3846 7.357737 1389576_at 10.12005 10.00802 10.25134 10.048639.885474 10.07426 9.457385 1382830_at 4.969063 4.957268 5.2023444.922326 4.876946 5.055368 5.370588 1374033_at 7.711859 7.6010997.685368 7.637296 7.383688 7.697378 6.834644 1376671_at 12.2229611.69939 11.60081 11.97408 11.76723 11.75523 10.7084 1387358_at 11.7406611.18677 11.28169 11.62427 11.25416 11.59928 10.33291 1388770_at11.15406 11.13059 11.0718 10.80027 10.56684 11.06096 9.817394 1371423_at9.826571 10.12291 9.900524 9.679627 9.372558 9.840867 8.9562641368271_a_at 7.22645 7.158662 7.382331 7.077927 7.005694 6.7919755.153542 1395460_at 8.253933 8.568113 8.555215 8.54373 8.015136 8.4537979.064542 1390825_at 9.079012 8.66244 8.833469 8.703624 8.561205 8.903077.850392 1372445_at 9.558017 9.656089 9.885727 9.489672 8.838308 9.568348.368073 1372697_at 8.465547 8.258319 8.321157 8.126768 8.0406848.284172 7.364254 1374327_at 5.086214 4.981402 5.08936 5.064869 5.1791525.313857 4.636872 1385595_at 7.413389 7.203759 7.354751 7.0551887.336935 7.428443 6.497058 1370554_at 10.96688 10.63323 11.0491810.86727 10.68507 10.94256 9.973723 1383009_at 6.912869 6.6647086.737424 6.795533 6.032179 6.359737 4.896072 1398473_at 9.7535519.703123 9.524262 9.416597 9.388871 9.461454 8.930461 1373296_a_at9.384805 9.125605 9.186713 8.814689 8.853889 8.798578 7.8161561371826_at 7.386995 7.635351 7.697299 7.448534 7.646439 7.5963888.253428 1371860_at 10.56361 10.56474 10.03409 10.3387 10.62167 10.264669.31406 1389724_at 7.923676 7.97331 7.905505 7.859257 7.659414 7.5162648.566793 1367731_at 9.359254 9.304589 9.260637 9.422495 9.3334729.523438 8.230864 1372098_at 8.296248 7.905817 8.032189 8.1919268.360776 8.035287 7.460235 1375675_at 6.832403 6.715793 6.5808386.815643 7.195003 7.519896 5.71638 1391391_at 4.143391 4.042431 3.9009494.018972 4.557771 3.926286 3.34483 1393203_at 8.509968 8.081169 8.1561458.383277 8.075688 8.017791 7.439902 1389140_at 11.42882 11.5404111.41288 11.33641 11.77431 11.23695 10.63705 1378079_at 8.7056228.561362 8.485119 8.859117 8.812967 8.496126 7.767726 1377414_at7.240502 6.928997 7.119189 7.130626 7.072199 7.13773 6.3776881376112_a_at 8.120983 7.953225 8.275113 8.471656 8.212972 8.5213768.864748 1380499_at 7.096902 7.555627 7.36757 7.296937 6.971908 7.7598798.262432 1387117_at 9.239842 8.627353 9.067328 9.07941 9.908435 9.0186077.679751 1372265_at 9.936615 9.480063 9.263571 9.708231 9.9295959.455903 8.375739 1372788_at 6.272475 6.507809 6.304112 6.3041666.228585 6.604101 7.070823 1389144_at 10.52908 10.17599 10.5065110.18955 10.31199 9.989998 9.457652 1397556_at 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1368665_at 8.3671558.427347 8.312457 8.634957 8.573368 8.627 8.591522 1388067_a_at 8.7965258.772141 8.861678 8.627837 8.698711 8.875414 8.620972 1390924_at 4.422034.827431 5.172974 4.99579 4.739177 4.999355 5.017769 1368123_at 7.9049517.636417 8.057934 7.928757 7.763832 7.584241 8.068762 1372393_at8.992121 9.00477 8.802998 9.196878 8.849224 9.182446 9.085267 1384943_at6.100576 6.412126 6.437269 7.188635 6.669894 6.461192 6.6922441380768_at 6.209552 6.235426 6.728205 6.988368 6.367614 6.8781347.231529 1388013_at 4.71294 4.794352 4.690289 4.654907 4.782202 4.943724.821069 1398241_a_at 5.370259 5.409038 5.330118 5.461689 5.2822155.543443 5.539157 1384207_at 5.664329 5.803087 5.644646 5.70154 5.5908475.646159 5.632695 1387617_at 6.774814 5.916818 6.981282 6.2751696.749048 6.402013 6.35743 1388745_at 6.360753 6.429884 6.35904 6.2223986.690005 6.16909 6.172013 1385975_at 3.655451 3.639901 3.687412 3.516733.546149 3.660697 3.594977 1392745_at 4.832234 4.963644 4.8743424.984741 5.003458 4.859814 4.681391 1378229_at 8.179664 8.01499 7.8062557.806977 7.963169 7.841969 7.765816 1395860_at 5.018488 4.6344364.740092 4.977493 5.101506 5.04169 5.202587 1380257_at 7.37725 7.4625117.578229 7.455303 7.616852 7.684983 7.511676 1383627_a_at 7.4113497.706995 8.290465 7.639293 7.480893 7.991505 8.165251 1371120_a_at4.816896 4.590357 4.56291 4.515408 4.621802 4.575861 4.476161 1373135_at6.538211 6.087747 6.38477 6.703653 6.634717 6.46332 6.487785 1368062_at8.801505 8.852804 8.826192 8.960214 8.947813 8.980855 8.601901AFFX-r2-Ec-bioC-3_at 9.18812 8.887714 8.903624 9.12256 9.526751 9.8145259.817275 1398909_at 9.716631 9.684194 9.495219 10.01092 9.8863529.904391 9.82862 1399074_at 9.086419 9.135042 9.203997 9.210174 8.9760069.272859 9.095237 1384370_at 5.498746 5.586697 5.537012 5.6960685.638748 5.571183 5.357013 1370253_at 11.15965 10.85646 11.0210311.26431 11.31469 11.33746 11.37567 1374357_at 7.858552 7.8522737.808009 8.27856 8.063117 8.079088 7.990019 1384344_at 6.80036 6.5449676.758 6.943233 7.119518 7.102233 6.875752 1396142_at 7.277484 6.9047967.287323 7.303102 7.318411 7.274101 7.296395 1371944_at 10.7223310.49927 10.44866 10.87346 10.88892 10.63346 10.4073 1378396_at 7.0315937.176079 7.288923 6.983694 7.010744 7.196433 7.658381 1376570_at10.82502 10.80457 10.96014 11.13391 10.96831 11.35412 11.321611371810_at 9.332541 9.056085 9.310855 9.045788 9.236917 9.0111998.847815 1367465_at 10.57096 10.19517 9.895014 10.4014 10.56095 10.3143110.0588 1376272_a_at 10.28879 9.932648 9.954964 10.36673 10.436569.988782 9.913219 1389178_at 8.721315 8.85939 8.843272 8.97333 8.5691288.967769 8.869086 1376745_at 7.18613 7.52318 7.382136 7.224264 7.0187127.200412 7.263262 1391527_at 6.846371 6.36652 6.613354 6.779794 6.9028376.574278 6.518157 1369656_at 6.176432 6.229931 6.233386 6.47454 6.1196696.529218 6.540164 1389045_at 6.481584 6.412969 6.254184 6.2971296.534825 6.641746 6.545324 1384950_at 6.5579 6.735608 6.679444 6.8189786.539319 6.526219 6.811573 1387027_a_at 8.509784 8.588066 8.484558.79372 8.451693 8.639001 8.678782 1370613_a_at 9.169934 8.9579949.050581 9.025818 9.028429 9.195828 8.945095 1392975_at 7.4126117.151055 7.388451 7.521015 7.50785 7.56331 7.583048 1396387_at 4.2110464.291444 4.070767 4.075371 4.090993 4.052181 4.015742

TABLE 7 Probeset cr50 > cont cr70 > cr50 upup cr50 < cont cr70 < cr50downdown 1 1395846_at true true TRUE false false 2 1390943_at true trueTRUE false false 3 1389844_at true true TRUE false false 4 1368247_attrue true TRUE false false 5 1374857_at true true TRUE false false 61370811_at true true TRUE false false 7 1397918_at true true TRUE falsefalse 8 1371294_at true true TRUE false false 9 1387307_at true trueTRUE false false 10 1373177_x_at true true TRUE false false 111396398_at true true TRUE false false 12 1374699_at true true TRUE falsefalse 13 1385606_at true true TRUE false false 14 1385365_at true trueTRUE false false 15 1385133_at true true TRUE false false 16 1375014_attrue true TRUE false false 17 1390982_at true true TRUE false false 181367904_at true true TRUE false false 19 1387048_at true true TRUE falsefalse 20 1379592_at true true TRUE false false 21 1389765_at true trueTRUE false false 22 1395731_at true true TRUE false false 23 1393963_attrue true TRUE false false 24 1396468_at true true TRUE false false 251398877_at true true TRUE false false 26 1371188_a_at true true TRUEfalse false 27 1392356_at true true TRUE false false 28 1369021_at truetrue TRUE false false 29 1383967_at true true TRUE false false 301367741_at true true TRUE false false 31 1378552_at true true TRUE falsefalse 32 1389472_at true true TRUE false false 33 1388270_at true trueTRUE false false 34 1383346_at true true TRUE false false 35 1391321_attrue true TRUE false false 36 1385699_at true true TRUE false false 371377627_at true true TRUE false false 38 1394507_at true true TRUE falsefalse 39 1393961_at true true TRUE false false 40 1378247_at true trueTRUE false false 41 1386669_at true true TRUE false false 42 1377129_attrue true TRUE false false 43 1379021_a_at true true TRUE false false 441375206_at true true TRUE false false 45 1398636_at true true TRUE falsefalse 46 1385808_at true true TRUE false false 47 1393873_s_at true trueTRUE false false 48 1385620_at true true TRUE false false 49 1387779_attrue true TRUE false false 50 1381510_at true true TRUE false false 511389203_at true true TRUE false false 52 1386186_s_at true true TRUEfalse false 53 1388438_at true true TRUE false false 54 1372191_at truetrue TRUE false false 55 1396301_x_at true true TRUE false false 561395364_at true true TRUE false false 57 1368338_at true true TRUE falsefalse 58 1388971_s_at true true TRUE false false 59 1389565_at true trueTRUE false false 60 1393988_at true true TRUE false false 61 1399032_attrue true TRUE false false 62 1385303_at true true TRUE false false 631384064_at true true TRUE false false 64 1387511_at true true TRUE falsefalse 65 1372646_at false false true true TRUE 66 1368474_at false falsetrue true TRUE 67 1376624_at false false true true TRUE 68 1388879_atfalse false true true TRUE 69 1391563_at false false true true TRUE 701387029_at false false true true TRUE 71 1387854_at false false truetrue TRUE 72 1372585_at false false true true TRUE 73 1397173_at falsefalse true true TRUE 74 1368558_s_at false false true true TRUE 751383589_at false false true true TRUE 76 1380962_at false false truetrue TRUE 77 1395519_at false false true true TRUE 78 1381993_at falsefalse true true TRUE 79 1388996_at false false true true TRUE 801368751_at false false true true TRUE 81 1389553_at false false truetrue TRUE 82 1387796_at false false true true TRUE 83 1369132_at falsefalse true true TRUE 84 1382146_at false false true true TRUE 851393008_at false false true true TRUE 86 1368064_a_at false false truetrue TRUE 87 1397670_at false false true true TRUE 88 1388116_at falsefalse true true TRUE 89 1370959_at false false true true TRUE 901371677_at false false true true TRUE 91 1381556_at false false truetrue TRUE 92 1379314_at false false true true TRUE 93 1371015_at falsefalse true true TRUE 94 1380822_at false false true true TRUE 951377086_at false false true true TRUE 96 1375350_at false false truetrue TRUE 97 1368829_at false false true true TRUE 98 1370155_at falsefalse true true TRUE 99 1391916_at false false true true TRUE 1001387893_at false false true true TRUE 101 1371614_at false false truetrue TRUE 102 1390510_at false false true true TRUE 103 1384310_at falsefalse true true TRUE 104 1379357_at false false true true TRUE 1051373410_at false false true true TRUE 106 1389164_at false false truetrue TRUE 107 1377751_at false false true true TRUE 108 1388054_a_atfalse false true true TRUE 109 1387570_at false false true true TRUE 1101368399_a_at false false true true TRUE 111 1382960_at false false truetrue TRUE 112 1384558_at false false true true TRUE 113 1377353_a_atfalse false true true TRUE 114 1384311_at false false true true TRUE 1151382028_at false false true true TRUE 116 1389718_at false false truetrue TRUE 117 1371483_at false false true true TRUE 118 1372146_at falsefalse true true TRUE 119 1379932_at false false true true TRUE 1201368332_at false false true true TRUE 121 1389413_at false false truetrue TRUE 122 1381452_at false false true true TRUE 123 1375982_at falsefalse true true TRUE 124 1387795_at false false true true TRUE 1251382711_at false false true true TRUE 126 1373882_at false false truetrue TRUE 127 1375729_at false false true true TRUE 128 1393217_at falsefalse true true TRUE 129 1391610_at false false true true TRUE 1301376071_at false false true true TRUE 131 1370827_at false false truetrue TRUE 132 1383453_at false false true true TRUE 133 1378474_at falsefalse true true TRUE 134 1372922_at false false true true TRUE 1351373891_at false false true true TRUE 136 1376749_at false false truetrue TRUE 137 1376575_at false false true true TRUE 138 1379055_x_atfalse false true true TRUE 139 1377171_at false false true true TRUE 1401391462_at false false true true TRUE 141 1377640_at false false truetrue TRUE 142 1382659_at false false true true TRUE 143 1373944_at falsefalse true true TRUE 144 1369186_at false false true true TRUE 1451393866_at false false true true TRUE 146 1388936_at false false truetrue TRUE 147 1390914_at false false true true TRUE 148 1391428_at falsefalse true true TRUE 149 1373577_at false false true true TRUE 1501370280_at false false true true TRUE 151 1394101_at false false truetrue TRUE 152 1372013_at false false true true TRUE 153 1391030_at falsefalse true true TRUE 154 1390440_at false false true true TRUE 1551391211_at false false true true TRUE 156 1368156_at false false truetrue TRUE 157 1390638_at false false true true TRUE 158 1375966_at falsefalse true true TRUE 159 1397536_at false false true true TRUE 1601375378_at false false true true TRUE 161 1384180_at false false truetrue TRUE 162 1381504_at false false true true TRUE 163 1381577_at falsefalse true true TRUE 164 1392705_at false false true true TRUE 1651397221_s_at false false true true TRUE 166 1372947_at false false truetrue TRUE 167 1375523_at false false true true TRUE 168 1370583_s_atfalse false true true TRUE 169 1369648_at false false true true TRUE 1701391106_at false false true true TRUE 171 1378269_at false false truetrue TRUE 172 1371241_x_at false false true true TRUE 173 1376660_atfalse false true true TRUE 174 1379274_at false false true true TRUE 1751388789_at false false true true TRUE 176 1371202_a_at false false truetrue TRUE 177 1383529_at false false true true TRUE 178 1390427_at falsefalse true true TRUE 179 1377950_at false false true true TRUE 1801379683_at false false true true TRUE 181 1368822_at false false truetrue TRUE 182 1389305_at false false true true TRUE 183 1382660_at falsefalse true true TRUE 184 1387690_at false false true true TRUE 1851372587_at false false true true TRUE 186 1369633_at false false truetrue TRUE 187 1370333_a_at false false true true TRUE 188 1392856_atfalse false true true TRUE 189 1391551_at false false true true TRUE 1901388903_at false false true true TRUE 191 1371875_at false false truetrue TRUE 192 1372332_at false false true true TRUE 193 1374224_at falsefalse true true TRUE 194 1371040_at false false true true TRUE 1951379677_at false false true true TRUE 196 1394059_s_at false false truetrue TRUE 197 1368658_at false false true true TRUE 198 1389690_at falsefalse true true TRUE 199 1379652_at false false true true TRUE 2001374700_at false false true true TRUE 201 1379482_at false false truetrue TRUE 202 1394012_at false false true true TRUE 203 1396957_at falsefalse true true TRUE 204 1397167_at false false true true TRUE 2051376747_at false false true true TRUE 206 1389006_at false false truetrue TRUE 207 1388544_at false false true true TRUE 208 1378243_at falsefalse true true TRUE

TABLE 9 Group Predication Table from Systat Discrim. Analysis using 10genes listed in text of update. Animal Actual GRP Predicted GRP 1 1.0001.000 2 1.000 1.000 3 1.000 1.000 4 1.000 1.000 5 1.000 1.000 6 1.0001.000 7 1.000 1.000 8 1.000 1.000 9 2.000 2.000 10 2.000 2.000 11 2.0002.000 12 2.000 2.000 13 2.000 2.000 14 3.000 3.000 15 3.000 3.000 163.000 3.000 17 3.000 3.000 18 3.000 3.000 19 4.000 4.000 20 4.000 4.00021 4.000 4.000 22 4.000 4.000 23 4.000 4.000 24 4.000 4.000 Group (GRP)1 = control GRP2 = 50% caloric restriction GRP3 = 70% caloricrestriction GRP4 = High Fat diet

TABLE 10 Probeset SSRI SSRI SSRI SSRI SSRI SSRI C 1382608_at 5.4928925.536467 5.440813 5.641229 5.553487 5.572907 5.323105 1376218_a_at4.961073 5.159801 4.667357 4.873284 4.561898 4.552214 5.7494711386519_x_at 7.187885 7.294603 7.082242 7.037942 7.202921 7.1260057.601578 1385442_at 7.159886 7.404339 6.996945 6.879263 6.9199686.943116 7.831252 1384923_at 6.976946 7.200037 6.817507 6.9389166.836614 6.982019 7.388793 1385163_at 6.063322 5.993012 6.0451615.954846 5.884809 6.124244 5.653232 1383659_a_at 5.774419 5.5190355.386271 5.431161 4.833011 6.495673 6.266045 1393517_at 6.6310466.746358 6.287015 6.482644 6.515204 6.633106 7.091107 1376289_at3.746401 3.74974 3.659435 3.77225 3.709668 3.697027 3.470574 1390090_at7.476481 7.464459 7.498371 7.392979 7.300129 7.578367 6.8558261379140_at 4.025837 4.280388 4.108266 3.886397 4.070737 4.0786844.796397 1381966_at 8.360305 8.854557 8.773542 8.518282 8.7596158.756927 9.646637 1378355_a_at 5.806788 6.412462 5.853144 5.5356175.776693 6.036624 7.608109 1377123_at 8.957729 9.068757 8.7288168.818872 8.853459 8.789082 9.154175 1398571_x_at 5.476362 5.7832645.338547 5.581326 5.637951 5.597321 6.85281 1383472_at 3.95501 3.9511483.984368 4.032821 3.886509 3.898694 3.699795 1383900_at 4.7422124.616846 4.606327 4.705032 4.74939 4.764865 4.517066 1382015_at 7.6491757.911227 7.375985 7.558502 7.728075 7.549806 8.304304 1384467_at8.339893 8.506768 8.417856 8.05848 8.062486 8.234164 8.586584 1382825_at5.701211 6.303403 6.179596 5.770345 6.003744 5.788324 6.4123771395990_at 7.226975 7.567221 7.454375 7.384037 7.119715 7.2394667.906828 1376844_at 3.958214 3.91987 4.036005 4.210816 4.082233 4.213833.793962 1367978_at 5.913543 6.324466 5.573653 5.778349 5.9440675.841989 6.445117 1387406_at 6.009577 6.243269 5.981099 5.9811925.9156698 6.086563 6.552047 1379110_at 3.96473 4.036266 3.7394733.917379 3.885783 3.803709 4.3956561 1381122_at 5.405765 5.2188065.498901 5.147761 5.433531 5.211904 4.704723 1381872_at 6.4981827.027084 7.041754 6.737296 6.910882 6.996371 7.684974 1393266_at 4.990295.173955 4.982205 4.609065 4.823981 4.636297 5.661941 1372462_at 7.912457.819118 7.863875 7.873258 6.183853 8.214012 8.489119 1394498_at5.625738 5.476476 5.77752 5.780313 5.589403 5.687828 5.354906 1381941_at7.9719 8.218287 7.48277 7.553401 7.612148 7.329846 8.887315 1397738_at4.15853 4.153792 4.198277 4.196809 4.130645 4.270782 4.042414 1397834_at6.222785 6.440389 5.751763 5.565274 5.809979 5.977959 6.9313941373925_at 6.767744 6.886409 6.335062 6.194636 6.159356 6.3822437.138185 1384374_at 6.358261 6.642625 6.364911 5.886558 6.42059 6.362477.089011 1397187_at 5.846689 6.088335 6.023635 5.914559 5.9103285.885615 6.251108 1368985_at 4.724642 4.454151 4.645631 4.715157 4.588144.472289 4.27078 1386414_at 6.861174 7.195748 6.931775 7.199033 7.2492047.033052 7.604695 1377750_at 8.621961 9.024142 8.834947 8.8896389.137156 8.948241 7.862024 1372514_s_at 8.136352 8.210145 8.0711958.128063 7.74062 8.133797 8.385963 1387459_at 3.483577 3.638799 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3.247869 3.335784 3.303979 3.31902 3.327817 3.3489281383443_at 5.683651 5.567135 5.754669 5.467944 5.751992 5.6774035.701218 1378318_at 7.344914 7.180416 7.153283 7.37251 7.28878 7.6710097.572664 1370521_at 8.445812 8.335108 8.321042 8.443235 8.48602 8.3515278.365915 1376294_at 8.240748 8.136396 8.121804 8.206327 8.0313897.939353 7.843639 1398025_at 7.378956 7.276747 7.364328 7.10214 7.1717687.094738 7.304103 1393939_at 4.455979 4.321684 4.388084 4.3846654.239433 4.385835 4.367218 1390649_at 7.938102 7.687889 7.6733247.791348 7.858171 7.491383 7.527008 1383309_at 8.849448 8.6899328.969284 8.891145 8.933948 8.617682 8.604857 1373319_at 9.0548329.237388 9.183479 9.331507 9.182054 9.351879 9.526916 1372141_at9.138563 9.133975 9.291849 9.34714 9.239232 9.295156 9.670249 1368083_at8.131899 7.967377 8.205659 8.272071 8.390661 8.145126 8.2216271371435_at 11.00867 10.90612 11.23199 11.07677 10.98521 11.2702311.55239 1389917_at 5.655532 5.424886 5.451375 5.570937 5.415385 5.45355.45669 1375407_at 4.146777 4.198401 4.162417 4.179388 4.179573 4.2100674.246474 1374112_at 6.447901 6.478707 6.686114 6.529024 6.5000936.600799 6.615228 1374739_at 8.910156 8.84001 9.070197 9.07402 8.8582938.669296 8.599008 1389095_at 4.79639 4.404411 4.732173 4.906512 5.0267444.47297 4.326963 1393104_at 5.975915 6.598068 6.661273 6.589076 6.1118026.522552 6.20425 1397676_at 4.932901 5.266384 5.715198 5.111778 5.2742065.345541 5.855012 1381286_at 5.782027 5.606054 5.685497 5.4985015.475041 5.605097 5.508228 1377028_at 6.24998 5.820455 6.063891 5.9709416.061626 5.739891 6.085501 1391078_at 8.106426 8.271168 8.7401648.604317 8.221337 9.078712 9.316119 1388396_at 8.582576 8.4676398.632741 8.876118 8.642394 8.157713 8.432301 1381074_at 4.7768574.698159 4.460426 4.412136 4.875408 4.545246 4.428375 1377210_at5.248109 4.862723 5.700934 5.485466 5.014901 5.171668 5.3724691370180_at 10.05871 9.922619 10.49934 10.19777 9.827023 10.4044110.42711 1370766_at 4.942443 4.938172 5.166151 5.488656 5.322127 4.712385.042534 1383670_at 6.710051 6.607325 6.621336 6.709491 6.7120937.383305 7.343236 1379827_at 7.363442 6.822804 7.052309 7.07748 7.0799977.625611 7.462587 1377746_at 6.748035 6.562857 6.854945 6.8292646.771986 6.746288 6.820429 1393989_at 7.171054 6.991178 7.09134 6.9630717.056965 6.799059 6.583873 1373804_at 6.825274 6.702404 7.2084957.237738 6.824612 7.527008 7.716825 1380454_at 6.241324 5.983879 6.009355.947613 5.973758 6.055284 5.955546 1373702_at 8.33185 8.305246 8.1615948.513912 8.321965 7.81442 7.873549 1381130_at 3.90718 4.131394 4.0620934.00716 3.997464 4.159053 4.070978 1385113_at 7.347283 7.428331 7.301047.161173 7.416947 7.087856 7.051209 1387136_at 6.857859 6.8793076.715853 6.835796 6.916941 6.910151 6.800685 1383300_at 8.0060828.006505 8.361511 8.2749 8.022177 8.359105 8.558606 1367877_at 10.9015611.00311 11.20721 11.24657 10.7225 10.35455 9.967765 1369754_a_at 8.03928.245252 7.920427 7.959489 8.000222 8.032917 8.209331 1392950_at3.887129 3.883732 3.808656 3.812032 3.820393 3.88542 3.706304 1388091_at4.883372 4.895909 4.860044 4.659865 4.763117 5.100578 5.0813731385676_at 7.767475 7.783984 7.600493 7.923105 7.825277 7.9572927.848675 1370682_at 5.233868 5.32624 5.095332 5.170874 5.242305 5.481555.263955 1394790_at 6.517335 6.383183 6.546073 6.377263 6.5209266.432519 6.411025 1399108_at 7.197649 7.339689 7.478999 7.3204917.149115 7.20594 7.58427 1367856_at 9.22695 9.529068 9.365102 9.3850489.389596 9.76226 9.547979 1384849_at 4.388693 4.320512 4.282258 4.3231054.50827 4.489202 4.609522 1389938_at 3.470526 3.407639 3.488442 3.4999093.515915 3.490367 3.425181 1395316_at 7.32684 7.191957 7.672393 7.0753637.224963 7.175964 7.116155 1388390_at 10.41323 10.51712 10.485 10.6288510.5942 10.75473 10.7773 1393539_at 5.341786 5.529504 5.246557 5.2545295.362529 5.602461 5.540961 1373396_at 9.154677 8.864159 9.2029269.102311 8.932804 8.366235 8.549971 1384528_at 6.294633 6.6395336.851434 6.655983 6.499612 7.042111 7.278227 1379963_at 6.9460896.646229 6.730348 6.720061 6.709743 6.949842 6.90215 1378992_at 3.7152713.630485 3.611331 3.743885 3.56719 3.654911 3.629206 1391376_at 7.6497737.981893 7.683304 7.517512 7.49073 7.601751 7.527206 1385137_at 6.4869326.690671 6.524926 6.506544 6.656693 6.51492 6.473502 1390892_at 5.5964725.604225 5.50656 5.408264 5.570845 5.5082 5.409615 1397956_at 6.0131056.030972 6.260479 5.900233 5.673819 6.03905 6.140571 1398208_s_at6.851001 6.896828 7.111651 6.972396 6.89232 7.05601 7.049933 1377621_at9.057845 9.147932 9.271816 8.936416 8.844168 9.113891 9.0586891370293_at 5.002656 5.145953 4.947144 4.866258 4.888348 5.1554534.853477 1382513_at 6.674163 6.665315 6.480641 6.607116 6.7365276.658752 6.65185 1386125_at 6.722093 6.815417 6.393768 6.646826 6.9152036.55516 6.508228 1383599_at 8.080652 7.625851 7.843413 7.828882 8.1269029.642324 9.524186 1369775_at 8.114099 8.46892 8.776746 8.329269 7.8972939.18486 9.188358 1387693_a_at 6.34591 5.564146 5.898449 6.2983156.189505 6.092007 5.62898 1389213_at 8.130876 8.027784 7.744935 7.9142178.246469 8.134782 7.863013 1391509_at 8.435513 8.439677 8.9289738.686683 8.507594 8.573678 8.37123 1398136_at 4.108807 4.099462 4.0345064.046964 4.062351 4.154086 4.099306 AFFX-r2-Ec-bioC-5_at 9.3366549.16583 9.068818 9.341125 9.591659 10.03402 10.11081 1385386_at 3.8795263.886862 3.72369 3.939486 3.964475 3.997111 3.855288 1373647_at 8.3713928.229571 8.671911 8.447359 8.268229 8.235445 8.429099 1390477_at5.454602 5.297205 5.407532 5.152992 5.57538 5.332575 5.384387 1388131_at5.882669 5.853117 5.898871 5.700392 5.652823 5.852608 5.9418061382670_at 8.607625 8.306811 8.398667 8.687534 8.345867 8.2197 8.5521411384137_at 4.248103 4.469068 4.06801 4.20896 4.162241 4.320374 4.2761341374707_at 8.157394 7.84171 8.125784 8.108103 8.19244 7.698878 7.8182951381492_at 3.39466 3.35917 3.314776 3.410916 3.370553 3.46529 3.380421389599_at 7.149853 6.872076 6.833596 7.063181 7.294202 6.8167066.740096 1380175_at 5.160696 4.961601 5.291116 5.161053 5.1602215.030026 5.212806 1370983_at 5.629613 5.842618 5.666426 5.47773 5.5722715.443443 5.688576 1396130_at 3.996715 4.120051 3.889792 3.8147123.974254 3.921034 3.958764 1387914_at 7.113919 7.094792 6.9700477.202853 7.171078 6.742761 7.040104 1368824_at 8.825603 8.8553789.531276 9.130224 8.806001 9.975893 10.39037 1381456_at 5.5104725.294116 5.39214 5.361957 5.478666 5.537828 5.46222 1375178_at 5.8607355.693961 5.836406 5.573762 5.872586 5.941907 5.899785 1377441_at4.926312 4.73964 4.842323 4.89651 4.794061 4.800346 4.851957 1385290_at5.912105 5.666417 5.934266 5.764757 5.85546 6.049654 5.921483 1368198_at6.200761 5.96258 5.963996 5.90697 5.996109 5.98626 5.902249 1370253_at11.14977 10.85983 11.06 11.28014 11.35627 11.36815 11.38424 1378906_at4.061325 4.197327 4.19609 4.263281 4.048104 4.09945 4.154332 1393438_at5.321704 5.380563 5.359406 5.376186 5.366238 5.286912 5.1854571376661_at 9.242853 8.930118 9.16586 9.212681 9.040385 8.674148 8.6462031387822_at 6.542111 6.445634 6.117231 6.626474 6.633556 6.308574 6.364651391283_at 5.833841 5.874396 5.96024 5.702392 5.598074 5.89814 5.7623151379691_at 5.194612 5.150488 5.649781 5.355132 5.020573 5.42467 5.747831378200_at 3.49684 3.655582 3.453484 3.611351 3.53718 3.652948 3.5894231391962_at 3.905926 3.859192 3.835026 3.837576 3.857248 3.9176693.892958 1374608_at 9.770124 9.608656 9.788637 9.721411 9.5562869.834954 9.733287 1390406_at 10.34409 10.3557 10.50253 10.18781 10.4578110.31091 10.63144 1394343_s_at 3.577921 3.611894 3.498068 3.5863763.587633 3.604372 3.615012 1370317_at 8.087234 8.10199 8.255473 8.3076778.149681 8.490723 8.609283 1385391_at 3.906025 4.128003 4.1175344.065756 4.119367 4.247722 4.378803 1382156_at 4.656724 4.812004 4.826264.711744 4.874337 4.95205 4.751615 1377365_at 4.943028 5.013649 4.8181945.177219 5.083958 4.986952 5.169062 1397587_at 7.541917 7.10395 7.0717077.170173 7.225319 6.495967 6.76673 1383054_at 8.807657 9.017428 9.0704398.990953 8.711281 9.325601 9.41996 1398949_at 8.606254 8.576337 8.663588.940726 8.595456 8.818478 8.839183 1379822_at 4.426261 4.4870984.337195 4.482956 4.602365 4.653999 4.927613 1373572_at 7.8681077.821535 7.630051 7.99082 8.104034 8.16109 7.916932 1395817_at 7.3596727.160284 7.247123 7.595406 7.497324 7.412344 7.191531 1387694_at4.568289 4.709052 4.716824 4.567781 4.66874 4.59178 4.597032 1384573_at8.900946 8.97017 9.056015 9.080516 8.76583 9.187965 9.330243 1385967_at7.8281 7.603817 7.783287 7.852722 7.73947 7.586877 7.564309 1397934_at8.298753 8.220983 8.121526 8.187293 8.222358 8.186979 8.2000051380887_at 4.806778 4.819667 4.710192 4.69149 4.822587 4.923829 4.7029491390592_at 7.922063 8.041783 8.387599 8.099686 7.908114 8.7827918.955466 1394383_at 6.225513 6.542422 6.277278 5.892306 6.1548076.123525 6.229771 1376622_at 9.17885 9.105556 9.15757 9.007202 8.8279368.849989 8.682105 1385074_at 5.671337 5.562711 5.767921 5.52647 5.1945235.636218 5.513816 1385790_at 8.873689 8.702837 8.93601 8.711004 8.7969278.832008 8.617366 1371174_s_at 6.567701 6.371281 6.498948 6.1752626.345222 6.398374 6.404599 1387836_at 6.084263 6.194557 5.7595536.332689 6.223032 6.426774 6.244026 1370918_a_at 11.30863 11.279211.24724 11.36628 11.45237 11.48919 11.41651 1398486_at 4.3551094.744269 5.03229 4.74111 4.489842 5.709248 5.543765 1397268_at 5.1566855.261241 5.068187 4.989594 5.172585 4.920382 5.027522 1393428_at6.022873 6.1025 6.339632 6.136967 6.165123 5.934912 6.608032 1391678_at7.246252 7.316186 7.365494 7.474511 7.386948 7.42633 6.897458 1388363_at8.334143 8.136501 8.387347 8.484121 8.155221 8.23048 8.22643 1388669_at7.592953 7.652917 7.716242 7.739342 7.557408 7.505974 7.687241394887_x_at 4.368967 4.298035 4.252718 4.257702 4.269459 4.2510224.360876 1384367_at 5.722115 5.628084 5.603972 6.024885 5.7348425.669305 5.559763 1383329_at 5.894521 5.614171 5.919978 5.6691085.593446 5.825996 5.854211

TABLE 11 T-val df Probe set Gene Title Gene Symbol contr.vs.5 contr.vs.51367901_at glucuronidase, beta Gusb 2.34973 8 1368264_at peroxisomalbiogenesis factor 6 Pex6 4.697176 8 1368356_a_at type 1 tumor necrosisfactor receptor shedding Arts1 2.94295 7 aminopeptidase regulator1369725_at centaurin, alpha 2 Centa2 2.385189 11 1370237_atL-3-hydroxyacyl-Coenzyme A dehydrogenase, short chain Hadhsc 2.587076 71372806_at vacuolar protein sorting 35 (mapped) Vps35_mapped 3.396093 101373392_at TPA regulated locus Tparl 2.297901 10 1374076_at similar tohypothetical protein FLJ34389 (predicted) RGD1305243_predicted 2.4888688 1374540_at cell division cycle associated 7 Cdca7 8.391325 111375297_at similar to RIKEN cDNA 0610008C08 (predicted)RGD1565289_predicted 4.693393 11 1377021_at Transcribed locus — 4.46636510 1377263_at cofactor required for Sp1 transcriptional activation,subunit 9 Crsp9_predicted 2.847021 6 (predicted) 1377866_a_atgeranylgeranyl diphosphate synthase 1 Ggps1 2.359719 10 1378127_atcullin 2 (predicted) Cul2_predicted 3.329496 6 1379488_at TP53regulating kinase (predicted) Trp53rk_predicted 3.065082 6 1381229_at PRdomain containing 2, with ZNF domain (mapped) Prdm2_mapped 2.490891 101383635_at DEAD (Asp-Glu-Ala-Asp) box polypeptide 59 Ddx59 2.268593 91387334_at mast cell protease 6 Mcpt6 2.814419 9 1388304_at NADHdehydrogenase (ubiquinone) 1 beta subcomplex, 5 Ndufb5_predicted3.089763 9 (predicted) 1388465_at Transcribed locus — 2.22618 111388660_at malignant T cell amplified sequence 1 Mcts1 2.683183 111388926_at Ectonucleotide pyrophosphatase/phosphodiesterase 5 Enpp52.520732 11 1389111_at Transcribed locus — 5.97356 11 1389325_at similarto programmed cell death 10 MGC72992 2.713215 10 1389833_at Sulfatasemodifying factor 1 (predicted) Sumf1_predicted 2.260779 10 1390687_atpleckstrin Plek 4.190275 8 1391714_at pleiomorphic adenoma gene 1 Plag13.379754 9 1392286_at Transcribed locus — 2.766072 11 1393226_atTranscribed locus — 3.139333 9 1393310_at Transcribed locus — 4.556303 71393980_at Transcribed locus — 5.043674 10 1394077_at Rho family GTPase3 Rnd3 2.445492 10 1394340_at inositol polyphosphate-1-phosphatase Inpp13.193406 8 1394591_at zinc finger protein 207 Zfp207 4.155383 101367843_at aldo-keto reductase family 7, member A2 (aflatoxin aldehydeAkr7a2 3.493363 9 reductase) 1368418_a_at ceruloplasmin Cp 4.225434 111373607_at ST3 beta-galactoside alpha-2,3-sialyltransferase 3 St3gal32.830407 11 1373627_at Similar to putative phosphoinositide5-phosphatase type II; LOC287533 2.45387 11 C62 1374366_at solutecarrier family 39 (zinc transporter), member 4 Slc39a4_predicted2.449188 11 (predicted) 1374415_at polymerase (RNA) III (DNA directed)polypeptide E Polr3e_predicted 3.423041 7 (predicted) 1374454_atProtein-L-isoaspartate (D-aspartate) O-methyltransferasePcmtd2_predicted 2.510643 10 domain containing 2 (predicted) 1374614_atkelch repeat and BTB (POZ) domain containing 4 (predicted)Kbtbd4_predicted 2.369813 8 1374770_at N-acylsphingosine amidohydrolase1 Asah1 2.644989 11 1375191_at RGD1564011 (predicted)RGD1564011_predicted 2.201641 11 1376745_at Mss4 protein Mss4 2.45043 71379314_at — — 3.922643 11 1379496_at RT1 class lb, locus Aw2 RT1-Aw23.905773 11 1383571_at hypothetical protein LOC303515 LOC303515 2.73192411 1383789_at Transcribed locus — 2.475547 9 1385639_at — — 2.411824 101387021_at wild-type p53-induced gene 1 Wig1 2.593846 7 1389582_at — —3.019152 11 1389718_at Transcribed locus — 3.754451 11 1392953_at — —3.00961 8 1393037_at — — 2.272651 11 1393245_at Phytanoyl-CoAhydroxylase Phyh 4.432412 9 1399108_at similar to expressed sequenceAV340375 RGD1308959 2.219593 11 p-val T-val df_contr.vs. p-val T-val 5vs. df p-val 5 vs. Mean Probe set contr.vs.5 Contr.vs_10 10 contr.cs.1010 5 vs. 10 10 Contr Mean 5% 1367901_at 0.046701 5.512363 7 8.95E−042.692259 6 0.035944 7.420203 6.974745 1368264_at 0.001547 7.560118 62.78E−04 2.52082 6 0.045237 6.259265 5.664209 1368356_a_at 0.0216225.28988 4 0.006129 2.588352 5 0.048934 9.55972 9.181831 1369725_at0.036168 4.52113 9 0.0014445 2.45629 6 0.049367 5.497342 5.0890611370237_at 0.036098 4.990147 4 0.0075429 2.671601 5 0.044263 8.7933438.480746 1372806_at 0.006816 4.811583 10 7.11E−04 2.466162 6 0.04871110.46183 10.13292 1373392_at 0.044413 5.144197 4 0.0067716 4.448717 30.021131 8.308305 8.164291 1374076_at 0.037589 5.51807 4 0.00526543.751059 4 0.019929 7.300542 6.97963 1374540_at 4.14E−06 13.50243 109.56E−08 4.273706 6 0.005242 6.195992 5.287047 1375297_at 6.57E−046.666884 10 5.59E−05 2.722782 6 0.034515 7.731478 6.937547 1377021_at0.001204 7.68836 9 3.04E−05 2.839884 6 0.029571 5.80011 5.1485721377263_at 0.029296 5.91322 5 0.0019703 2.475036 6 0.048128 7.4710236.737194 1377866_a_at 0.039972 4.71138 10 8.27E−04 4.026064 4 0.0157855.646626 5.273044 1378127_at 0.015817 6.525445 4 0.0028484 2.54369 60.043862 6.258107 5.628944 1379488_at 0.022081 8.042026 5 4.81E−043.750402 6 0.009505 5.228085 4.922934 1381229_at 0.031941 3.802602 80.0052173 2.537826 6 0.04421 5.346211 4.872466 1383635_at 0.0494775.90793 6 0.0010459 3.473082 6 0.013254 6.981191 6.626937 1387334_at0.020231 7.931182 8 4.65E−05 3.391524 4 0.027491 5.601581 5.2064321388304_at 0.012934 5.031626 7 0.0015106 3.612408 3 0.036442 10.122869.746815 1388465_at 0.047845 4.609294 10 9.66E−04 3.38009 6 0.0148566.549543 6.133349 1388660_at 0.021287 4.670909 9 0.0011671 2.929763 50.032642 8.623529 8.191288 1388926_at 0.028438 5.335912 10 3.30E−042.980559 6 0.024619 5.277582 4.893534 1389111_at 9.27E−05 5.94563 30.0095132 3.541052 3 0.038335 5.875325 5.420104 1389325_at 0.0218135.021052 10 5.21E−04 3.723483 5 0.013663 10.24563 9.919337 1389833_at0.047306 5.854823 7 6.28E−04 3.815016 6 0.008812 6.839621 6.4641761390687_at 0.003037 8.053889 5 4.78E−04 3.659266 6 0.010589 6.1054855.535644 1391714_at 0.00813 4.655716 9 0.0011924 3.156521 6 0.0196526.670053 5.858906 1392286_at 0.018355 4.578884 6 0.003775 2.85526 40.04615 5.585624 5.242275 1393226_at 0.011941 6.362825 9 1.31E−042.46958 6 0.048485 7.705027 6.778772 1393310_at 0.002616 7.140214 40.0020349 3.107414 5 0.026629 7.364799 6.579394 1393980_at 5.04E−047.18862 10 2.97E−05 3.874667 5 0.011705 5.991591 5.335233 1394077_at0.034523 5.820561 10 1.68E−04 2.778249 5 0.038983 7.018906 6.5160091394340_at 0.012738 5.333216 4 0.0059524 2.730803 5 0.041241 5.055114.704473 1394591_at 0.001963 6.584037 6 5.89E−04 3.252108 5 0.0226438.125942 7.429881 1367843_at 0.006794 6.510363 7 3.31E−04 3.009154 60.023726 8.276972 7.547364 1368418_a_at 0.001423 6.119508 8 2.83E−042.476306 6 0.048045 5.816824 5.33169 1373607_at 0.01636 4.710264 90.0011041 3.115436 4 0.035684 6.298338 5.956115 1373627_at 0.0320254.955513 8 0.0011132 3.032061 4 0.038702 6.526312 5.829701 1374366_at0.032292 4.133168 7 0.0043865 2.822719 4 0.047696 7.252498 6.5533851374415_at 0.01109 5.935718 4 0.0040387 2.860821 5 0.035372 6.8490026.356022 1374454_at 0.030879 4.646292 5 0.0056008 2.724148 5 0.0415696.083112 5.463531 1374614_at 0.04526 5.824873 8 3.94E−04 2.818489 60.030415 6.314496 5.867744 1374770_at 0.022789 5.234397 7 0.00120663.375706 5 0.019766 9.074708 8.620237 1375191_at 0.049943 4.16391 100.0019366 2.759861 6 0.03286 5.471081 5.007805 1376745_at 0.0440796.322446 8 2.27E−04 2.592822 6 0.041056 6.629539 6.082428 1379314_at0.002382 5.301394 6 0.0018274 2.787818 4 0.049422 6.970231 6.1945151379496_at 0.002452 6.909599 10 4.15E−05 2.467657 6 0.048612 5.198444.649908 1383571_at 0.019511 4.451128 10 0.001233 2.779463 6 0.032025.867879 5.339246 1383789_at 0.035248 4.783315 5 0.0049561 2.77602 50.039086 5.574571 5.342271 1385639_at 0.036569 4.022082 8 0.003832.936126 4 0.042553 4.981165 4.503729 1387021_at 0.035744 6.194133 74.48E−04 2.582999 6 0.041601 6.895168 6.437024 1389582_at 0.0116735.212483 8 8.10E−04 2.852321 5 0.035726 7.588214 6.741736 1389718_at0.003185 6.329516 8 2.26E−04 4.108077 4 0.014755 5.751838 5.0899681392953_at 0.016824 6.345901 6 7.17E−04 2.831348 6 0.029905 7.4354116.788869 1393037_at 0.044102 4.865021 10 6.56E−04 3.829033 6 0.0086697.020197 6.710681 1393245_at 0.001641 8.437993 10 7.36E−06 2.536255 60.044304 6.483711 5.646391 1399108_at 0.0484 4.479248 8 0.00205783.270939 4 0.030762 6.859582 6.436919 Probe set Mean 10% Contr < 5 5 <10 Contr < 5 c < 5 < 10 Contr > 5 5 > 10 Contr > 10 c > 5 > 101367901_at 6.431816 NO NO NO NO YES YES YES YES 1368264_at 5.303002 NONO NO NO YES YES YES YES 1368356_a_at 8.724713 NO NO NO NO YES YES YESYES 1369725_at 4.691663 NO NO NO NO YES YES YES YES 1370237_at 8.014916NO NO NO NO YES YES YES YES 1372806_at 9.969095 NO NO NO NO YES YES YESYES 1373392_at 7.589092 NO NO NO NO YES YES YES YES 1374076_at 6.175178NO NO NO NO YES YES YES YES 1374540_at 4.94827 NO NO NO NO YES YES YESYES 1375297_at 6.614794 NO NO NO NO YES YES YES YES 1377021_at 4.752157NO NO NO NO YES YES YES YES 1377263_at 5.97359 NO NO NO NO YES YES YESYES 1377866_a_at 4.808311 NO NO NO NO YES YES YES YES 1378127_at5.031834 NO NO NO NO YES YES YES YES 1379488_at 4.494457 NO NO NO NO YESYES YES YES 1381229_at 4.661432 NO NO NO NO YES YES YES YES 1383635_at6.017881 NO NO NO NO YES YES YES YES 1387334_at 4.848615 NO NO NO NO YESYES YES YES 1388304_at 9.267339 NO NO NO NO YES YES YES YES 1388465_at5.667039 NO NO NO NO YES YES YES YES 1388660_at 7.770533 NO NO NO NO YESYES YES YES 1388926_at 4.550642 NO NO NO NO YES YES YES YES 1389111_at4.793567 NO NO NO NO YES YES YES YES 1389325_at 9.571108 NO NO NO NO YESYES YES YES 1389833_at 5.77432 NO NO NO NO YES YES YES YES 1390687_at4.932622 NO NO NO NO YES YES YES YES 1391714_at 5.553782 NO NO NO NO YESYES YES YES 1392286_at 4.791402 NO NO NO NO YES YES YES YES 1393226_at6.077027 NO NO NO NO YES YES YES YES 1393310_at 5.833555 NO NO NO NO YESYES YES YES 1393980_at 4.943026 NO NO NO NO YES YES YES YES 1394077_at6.068581 NO NO NO NO YES YES YES YES 1394340_at 4.268504 NO NO NO NO YESYES YES YES 1394591_at 6.769234 NO NO NO NO YES YES YES YES 1367843_at6.866282 NO NO NO NO YES YES YES YES 1368418_a_at 5.049638 NO NO NO NOYES YES YES YES 1373607_at 5.590178 NO NO NO NO YES YES YES YES1373627_at 5.350663 NO NO NO NO YES YES YES YES 1374366_at 5.652028 NONO NO NO YES YES YES YES 1374415_at 5.780101 NO NO NO NO YES YES YES YES1374454_at 4.611595 NO NO NO NO YES YES YES YES 1374614_at 5.325021 NONO NO NO YES YES YES YES 1374770_at 7.95164 NO NO NO NO YES YES YES YES1375191_at 4.638899 NO NO NO NO YES YES YES YES 1376745_at 5.489871 NONO NO NO YES YES YES YES 1379314_at 5.514398 NO NO NO NO YES YES YES YES1379496_at 4.376474 NO NO NO NO YES YES YES YES 1383571_at 5.001663 NONO NO NO YES YES YES YES 1383789_at 4.98583 NO NO NO NO YES YES YES YES1385639_at 4.258831 NO NO NO NO YES YES YES YES 1387021_at 5.949945 NONO NO NO YES YES YES YES 1389582_at 6.297198 NO NO NO NO YES YES YES YES1389718_at 4.744662 NO NO NO NO YES YES YES YES 1392953_at 6.103489 NONO NO NO YES YES YES YES 1393037_at 6.383948 NO NO NO NO YES YES YES YES1393245_at 5.227239 NO NO NO NO YES YES YES YES 1399108_at 5.828719 NONO NO NO YES YES YES YES sig down Sig sig up and and spec Probe set sigSSRI Sig HF MMMCR sig up sig down spec alc alc 1367901_at NO NO NO NoYes NO YES 0.001679 1368264_at NO NO NO No Yes NO YES   7E−051368356_a_at NO NO NO No Yes NO YES 0.001058 1369725_at NO NO NO No YesNO YES 0.001786 1370237_at NO NO NO No Yes NO YES 0.001598 1372806_at NONO NO No Yes NO YES 0.000332 1373392_at NO NO NO No Yes NO YES 0.0009381374076_at NO NO NO No Yes NO YES 0.000749 1374540_at NO NO NO No Yes NOYES 2.17E−08 1375297_at NO NO NO No Yes NO YES 2.27E−05 1377021_at NO NONO No Yes NO YES 3.56E−05 1377263_at NO NO NO No Yes NO YES 0.001411377866_a_at NO NO NO No Yes NO YES 0.000631 1378127_at NO NO NO No YesNO YES 0.000694 1379488_at NO NO NO No Yes NO YES 0.00021 1381229_at NONO NO No Yes NO YES 0.001412 1383635_at NO NO NO No Yes NO YES 0.0006561387334_at NO NO NO No Yes NO YES 0.000556 1388304_at NO NO NO No Yes NOYES 0.000471 1388465_at NO NO NO No Yes NO YES 0.000711 1388660_at NO NONO No Yes NO YES 0.000695 1388926_at NO NO NO No Yes NO YES 0.00071389111_at NO NO NO No Yes NO YES 3.55E−06 1389325_at NO NO NO No Yes NOYES 0.000298 1389833_at NO NO NO No Yes NO YES 0.000417 1390687_at NO NONO No Yes NO YES 3.22E−05 1391714_at NO NO NO No Yes NO YES 0.000161392286_at NO NO NO No Yes NO YES 0.000847 1393226_at NO NO NO No Yes NOYES 0.000579 1393310_at NO NO NO No Yes NO YES 6.97E−05 1393980_at NO NONO No Yes NO YES  5.9E−06 1394077_at NO NO NO No Yes NO YES 0.0013461394340_at NO NO NO No Yes NO YES 0.000525 1394591_at NO NO NO No Yes NOYES 4.45E−05 1367843_at NO NO NO No Yes NO YES 0.000161 1368418_a_at NONO YES No Yes NO NO 6.84E−05 1373607_at NO NO YES No Yes NO NO 0.0005841373627_at NO NO YES No Yes NO NO 0.001239 1374366_at NO YES YES No YesNO NO 0.00154 1374415_at NO YES YES No Yes NO NO 0.000392 1374454_at NOYES NO No Yes NO NO 0.001284 1374614_at NO YES NO No Yes NO NO 0.0013771374770_at NO YES NO No Yes NO NO 0.00045 1375191_at NO YES YES No YesNO NO 0.001641 1376745_at NO YES YES No Yes NO NO 0.00181 1379314_at NONO YES No Yes NO NO 0.000118 1379496_at NO YES YES No Yes NO NO 0.0001191383571_at NO YES YES No Yes NO NO 0.000625 1383789_at NO YES NO No YesNO NO 0.001378 1385639_at NO YES NO No Yes NO NO 0.001556 1387021_at NOYES YES No Yes NO NO 0.001487 1389582_at NO YES YES No Yes NO NO0.000417 1389718_at NO NO YES No Yes NO NO 4.7E−05 1392953_at NO YES NONo Yes NO NO 0.000503 1393037_at NO YES NO No Yes NO NO 0.0003821393245_at NO YES NO No Yes NO NO 7.27E−05 1399108_at YES NO YES No YesNO NO 0.001489

TABLE 12 Gene T-val df p-val T-val Probe set Gene Title Symbolcontr.vs.5 contr.vs.5 contr.vs.5 Contr.vs_10 1370527_a_at casein kinase1, delta Csnk1d 2.986261 8 0.017433 3.973956 1380351_at — — 4.308549 110.001238 4.307602 1381613_at Transcribed locus — 5.680522 11 1.42E−045.946172 1384272_at Zinc finger protein 365 Zfp365 2.911772 5 0.0333315.77205 1384691_at Transcribed locus, weakly similar — 4.243576 50.008142 6.725371 to XP_577161.1 PREDICTED: similar to ORF2 consensussequence encoding endonuclease and reverse transcriptase minus RNaseH[Rattus norvegicus] 1384793_at — — 2.895417 6 0.027498 9.9382011388932_at laminin, alpha 5 Lama5 2.484535 9 0.034732 3.8737991391879_at Transcribed locus — 2.524571 6 0.045008 6.73664 df_contr.p-val T-val df 5 p-val Mean Probe set vs.10 contr.cs.10 5 vs. 10 vs. 105 vs. 10 Contr Mean 5% Mean 10% 1370527_a_at 8 0.004096 3.327782 60.01585 9.270172 9.839312 10.02957 1380351_at 3 0.023032 3.287598 30.046151 4.084842 4.281886 4.907576 1381613_at 3 0.009511 3.55257 30.038021 4.040707 4.29003 4.634067 1384272_at 3 0.010312 2.800243 60.040646 4.004522 4.22733 4.516728 1384691_at 3 0.006711 2.545145 60.043776 4.1106.3 4.649739 5.112041 1384793_at 9 3.77E−06 3.045839 50.02856 4.215733 4.484639 4.760827 1388932_at 10 0.00309  2.860363 60.028788 9.205238 9.683496 9.896758 1391879_at 6 5.21E−04 2.617131 60.039739 4.20034 4.546958 4.936622 Probe set Contr < 5 5 < 10 Contr < 5c < 5 < 10 Contr > 5 5 > 10 Contr > 10 c > 5 > 10 1370527_a_at YES YESYES YES NO NO NO NO 1380351_at YES YES YES YES NO NO NO NO 1381613_atYES YES YES YES NO NO NO NO 1384272_at YES YES YES YES NO NO NO NO1384691_at YES YES YES YES NO NO NO NO 1384793_at YES YES YES YES NO NONO NO 1388932_at YES YES YES YES NO NO NO NO 1391879_at YES YES YES YESNO NO NO NO sig down Sig sig up and and Probe set sig SSRI Sig HF MMMCRsig up sig down spec alc spec alc 1370527_a_at NO NO NO Yes No YES NO0.000276 1380351_at NO NO NO Yes No YES NO 5.72E−05 1381613_at NO NO NOYes No YES NO 5.41E−06 1384272_at NO NO NO Yes No YES NO 0.0013551384691_at NO NO NO Yes No YES NO 0.000356 1384793_at NO NO NO Yes NoYES NO 0.000785 1388932_at NO NO NO Yes No YES NO 0.001   1391879_at NOYES YES Yes No NO NO 0.001789

1. A method of diagnosing true low birth weight in an infant subjectcomprising (a) measuring the level of gene expression of a true lowbirth weight related gene in a subject sample; (b) comparing measuredexpression of the true low birth weight related gene in a controlsample; wherein a variation in gene expression characterized by ap-value of at least 0.05 between the subject sample and the controlsample indicates a diagnosis of true low birth weight.
 2. The method ofclaim 1, wherein the subject sample is derived from the placenta.
 3. Themethod of claim 2, wherein the subject sample is derived from the fetus.4. The method of claim 1, wherein measuring the level of gene expressionis performed by the group consisting of DNA chip and real-timepolymerase chain reaction.
 5. The method of claim 1, wherein the infantsubject is at risk of true low birth weight.
 6. The method of claim 5,wherein the infant subject at risk of true low birth weight exhibits acondition selected from the group consisting of poor maternal nutrition,maternal alcohol abuse, maternal tobacco abuse, maternal drug abuse,bacterial or viral infections, illness, and genetic factors.
 7. Themethod of claim 1, wherein the true low birth weight related gene isselected from the group consisting of genes encoding IGF, genes encodingIGF binding proteins, and genes encoding IGF receptors.
 8. The method ofclaim 7, wherein the genes are selected from the group consisting ofALS, CTGF/CCN2, Endocan, IGFBP-1, IGFBP-2, IGFBP-3, IGFBP-4, IGFBP-5,IGFBP-6, IGFBP-7, and Nov/CCN3.
 9. The method of claim 7, wherein thetrue low birth weight related gene is IGF1.
 10. The method of claim 1,wherein the true low birth weight related gene is selected from thegroup consisting of solute carrier 18 (member 2) probe set 1369132),vascular adhesion molecule 1 (probe set 1368474), collagen type 1 alpha(probe set 1388116), allograft inflammatory factor 1 (1368558),arachidonate 12 lipoxygenase (probe set 1387796).
 11. A kit fordiagnosing true low birth weight comprising at least one oligonucleotideprobe directed to a true low birth weight related gene; and a controlselected from the group consisting of a standard value, a controlsample, or a reference standard.
 12. A method of predicting the dietaryconditions during pregnancy in an infant comprising (a) measuring thelevel of gene expression of one or more genes related to a dietarycondition in a subject sample; (b) comparing measured expression of thegenes related to a dietary condition in a control sample; wherein avariation in gene expression characterized by a p-value of at least 0.05between the subject sample and the control sample indicates the presenceof a dietary condition.
 13. The method of claim 12, wherein the generelated to a dietary condition is selected from the group consisting ofsolute carrier 18 (member 2) (probe set 1369132), vascular adhesionmolecule 1 (probe set 1368474), collagen type 1 alpha (probe set1388116), allograft inflammatory factor 1 (1368558), arachidonate 12lipoxygenase (probe set 1387796).
 14. The method of claim 12, whereinthe gene related to a dietary condition is selected from the groupconsisting of peroxisome proliferation activated receptor (gamma) (probeset 1369179), fatty acid binding protein 4 (probe set 1368271),apolipoprotein C-1 (probe set 1368587), lectin (galactose binding,soluble 9) (probe set 1387027), and glia maturation factor beta (probeset 1387663).
 15. The method of claim 1, wherein the true low birthweight gene is a fetal alcohol syndrome related gene.
 16. The method ofclaim 15, wherein the fetal alcohol syndrome related gene is selectedfrom the group consisting of Gusb, Pex6, Arts1, Centa2, Hadhsc, Vps35(mapped), Tpar1, RGD1305243 (predicted), Cdca7, RGD1565289 (predicted),Crsp9 (predicted), Ggps1, Cul2 (predicted), Trp53rk (predicted), Prdm2(mapped), Ddx59, Mcpt6, Ndufb5 (predicted), Mcts1, Enpp5, MGC72992,Sumf1 (predicted), Plek, Plag1, Rnd3, Inpp1, Zfp207, Akr7a2, Cp,St3gal3, LOC287533, Slc39a4 (predicted), Polr3e (predicted), Pcmtd2(predicted), Kbtbd4 (predicted), Asah1, RGD1564011 (predicted), Mss4,RT1-Aw2, LOC303515, Wig1, Phyh, RGD1308959, Csnk1d, Zfp365, and Lama5.